Voice craft technology for textile printing press

Abstract

Present disclosure relates to a method and system for processing an audio signal to control an operation of a textile printing press device. Method comprising receiving an audio input signal from an operator via a microphone. The audio input signal comprises at least one machine-specific instruction. Thereafter, method comprising filtering the audio input signal. Subsequently, method comprising determining an authenticity of the audio input signal using a trained natural language processing model. Lastly, method comprising transmitting the audio input signal to a programmable logic controller of the textile printing press device for controlling the operation of the textile printing press device based on the determination. Method further comprises converting the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device.

Description

TITLE: VOICE CRAFT TECHNOLOGY FOR TEXTILE PRINTING PRESSTECHNICAL FIELD

[0001] The present disclosure generally relates to the field of textile printing press device. Particularly, but not exclusively, the present disclosure relates to a method and a system for processing an audio signal to control an operation of a textile printing press device.BACKGROUND

[0002] Textile printing presses are widely used in the manufacturing industry for applying intricate designs and patterns onto fabrics. These mechanical machines are typically huge in size and operate in fast-paced environments, often requiring continuous monitoring and timely interventions to ensure optimal performance and minimal downtime. However, traditional textile presses typically rely on visual indicators, such as lights or display screens, to communicate machine status and alarms and manual intervention from operators to operate / control these machines. Operation and control of these machines typically require direct manual intervention by human operators, who must monitor the indicators and take appropriate action. In noisy factory settings, visual indicators alone may not be sufficient, as operators or maintenance personnel might not always be in the line of sight or attentive to such indicators or signals. This reliance on visual cues and manual oversight can limit efficiency, increase the potential for human error, and reduce responsiveness in high-volume or automated production environments. Furthermore, manual intervention by operators is not always safe, particularly in noisy factory environments and in the presence of large-scale printing press machinery. Such conditions can impair communication, and increase the risk of accidents or operator injury.

[0003] Thus, there exists a need for an improved method and system for controlling an operation of textile printing presses and for overcoming the above-mentioned limitations of the conventional methods.

[0004] The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the disclosure and should not be taken as an acknowledgement or any form of suggestion that this information forms existing information already known to a person skilled in the art.SUMMARY

[0005] In an embodiment, the present disclosure relates to a method for processing an audio signal to control an operation of a textile printing press device. The method comprising receiving an audio input signal from an operator via a microphone. The audio input signal comprises at least one machinespecific instruction. Thereafter, the method comprising filtering the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices. Subsequently, the method comprising determining an authenticity of the audio input signal using a trained natural language processing (NLP) model. Lastly, the method comprising transmitting the audio input signal to a programmable logic controller (PLC) of the textile printing press device for controlling the operation of the textile printing press device based on the determination.

[0006] In another embodiment, the present disclosure relates to a system for processing an audio signal to control an operation of a textile printing press device. The system comprising at least one directional microphone array with an acoustic beamforming technology, and a controller communicatively connected to the at least one directional microphone array. The at least one directional microphone array with an acoustic beamforming technology is configured to receive an audio input signal from an operator via a microphone. The audio input signal comprises at least one machine-specific instruction. The controller is configured to filter the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices. Thereafter, the controller is configured to determine an authenticity of the audio input signal using a trained NLP model. Lastly, the controller is configured to transmit the audio input signal to a PLC of the textile printing press device for controlling the operation of the textile printing press device based on the determination.

[0007] In an embodiment, the method further comprises converting the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device.

[0008] In another embodiment, the system further comprises a PLC communicatively connected to the controller. The PLC is configured to convert the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device.

[0009] In an embodiment, the method further comprises obtaining a signal associated with an operational status of the textile printing press device from a display unit. Thereafter, the method comprises generating an audio output corresponding to the signal associated with the operationalstatus of the textile printing press device. The audio output comprises audible feedback for communicating the operational status associated with the textile printing press.

[0010] In another embodiment, the present disclosure provides audio device for a textile printing press device which providing an additional channel for real-time communication of operational status information. The audio device is configured to obtain a signal associated with the operational status of the textile printing press device from a display unit. Thereafter, the audio device is configured to generate an audio output corresponding to the signal associated with the operational status of the textile printing press device. The audio output comprises audible feedback for communicating the operational status associated with the textile printing press. This approach of providing the audio device in textile printing presses enhances operator interaction, improving productivity, and machine efficiency.[Oil] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.BRIEF DESCRIPTION OF DRAWINGS

[0012] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and methods in accordance with embodiments of the present subject matter are now described below, by way of example only, and with reference to the accompanying figures.

[0013] Fig. la shows an exemplary environment of providing an audio device, in accordance with an embodiment of the present disclosure.

[0014] Fig. lb shows an exemplary environment for processing an audio signal to control an operation of a textile printing press device, in accordance with another embodiment of the present disclosure.

[0015] Figs.2a-2d show an exemplary process flow for providing operational status of printing press device by an audio device, in accordance with an embodiment of the present disclosure.

[0016] Fig. 3 shows a method flowchart for providing operational status by an audio device, in accordance with an embodiment of the present disclosure.

[0017] Fig. 4a shows a detailed block diagram of a controller, in accordance with an embodiment of the present disclosure.

[0018] Fig. 4b shows a detailed block diagram of a programmable logic controller, in accordance with an embodiment of the present disclosure.

[0019] Fig. 5 illustrates a flowchart showing a method for processing an audio signal to control an operation of a textile printing press device, in accordance with an embodiment of the present disclosure.

[0020] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flowcharts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.DETAILED DESCRIPTION

[0021] The foregoing has broadly outlined the features and technical advantages of the present disclosure in order that the detailed description of the disclosure that follows may be better understood. It should be appreciated by those skilled in the art that the conception and specific embodiment disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure.

[0022] The novel features which are believed to be characteristic of the disclosure, both as to its organization and method of operation, together with further objects and advantages will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purposeof illustration and description only and is not intended as a definition of the limits of the present disclosure.

[0023] Particularly, the present disclosure relates to system and method for integrating audio output functionality into textile printing presses (also, referred as textile printing press device) to communicate machine (also, referred as textile printing press device) operational status, alarms, and operational indicators to operators or personnel in proximity to the textile printing press. The audio device may be operatively connected to a display unit of the textile printing press. In this manner, the present disclosure ensures that machine information is effectively conveyed in real-time, enhancing operational awareness and efficiency by performing three key functions. Firstly, the audio device may assist operators during job setup by providing auditory feedback for selections made on the display unit. The feedback may be provided to the operators and nearby personnel regarding changes such as mode adjustments or job transitions, improving communication and reducing errors in noisy or large production environments.

[0024] Second, the audio device may serve as an alarm system, emitting audio alerts for faults, malfunctions, or anomalies detected by a controller. This ensures that the operators are promptly notified of issues, such as low air pressure or system errors, even when the operators may not be observing the display unit, allowing for swift responses to operational status problems. Lastly, the audio device may communicate real-time performance metrics, including printing speedjob progress, and machine idle times, through audio notifications to the operators or personnel, thereby, enabling operators to monitor machine efficiency, make informed decisions, and improve overall productivity.

[0025] In another embodiment, the present disclosure relates to a system and a method for processing an audio signal to control an operation of a textile printing press device. The system comprising at least one directional microphone array with an acoustic beamforming technology, and a controller communicatively connected to the at least one directional microphone array. The at least one directional microphone array with an acoustic beamforming technology is configured to receive an audio input signal from an operator via a microphone. The audio input signal comprises at least one machine-specific instruction. The controller is configured to filter the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices. Thereafter, the controller is configured to determine an authenticity of the audio input signal using a trained natural language processing (NLP) model. Lastly, the controller is configured to transmit the audioinput signal to a PLC of the textile printing press device for controlling the operation of the textile printing press device based on the determination. The present disclosure reduces or eliminates the need for manual intervention by operators, particularly in noisy factory environments and in the presence of large-scale printing press machinery. By minimizing reliance on direct operator involvement, the present disclosure enhances overall safety, mitigates conditions that may impair communication, and lowers the risk of accidents or operator injury.

[0026] The NLP model including automatic speech recognition (ASR) model employed in the invention may comprise, without limitation, a neural acoustic model (e.g., convolutional neural networks, recurrent neural networks, transformers), a pretrained speech model (e.g., wav2vec, HuBERT, Whisper, or similar architectures), or a hybrid model that combines statistical approaches (e.g., hidden Markov models) with neural components. The training of the NLP model including the ASR model is carried out using established machine learning techniques known in the art, such as supervised learning with paired audio-text corpora, semi-supervised learning with unlabeled speech data, or transfer learning from pretrained speech encoders. Training data may include large corpora of speech recordings aligned with textual transcriptions, drawn from both general and domain-specific sources. Exemplary datasets suitable for training include: General speech corpora: LibriSpeech, Common Voice (Mozilla), TED-LIUM, VoxForge. Conversational datasets: Switchboard, Fisher English, CALLHOME. Domain-specific corpora: CHiME (noisy environments), AMI Meeting Corpus (multi-speaker meetings), MGB (broadcast media). Multilingual datasets: Multilingual LibriSpeech, GlobalPhone, MLS (Multilingual Speech). The training process typically involves preprocessing of audio signals (e.g., feature extraction, or learned embeddings), tokenization of textual transcriptions, and optimization of model parameters using gradient-based methods such as stochastic gradient descent or Adam. Evaluation against held-out validation datasets ensures convergence and generalization. Performance of the NLP model including the ASR model may be assessed using standard evaluation metrics such as word error rate (WER), character error rate (CER), or domain-specific accuracy measures. These methods, datasets, and evaluation practices are well established in the field of NLP and ASR and provide sufficient guidance for a skilled person to implement the NLP model including the ASR model.

[0027] Fig. la shows an exemplary environment of providing an audio device, in accordance with an embodiment of the present disclosure.

[0028] The exemplary environment 100a comprises an audio device (also, referred as audio output device) 101, a display unit (also, referred as touch screen display unit) 103, and a controller (also, referred as main logic controller device) 105. In an embodiment, a text-to-speech device 107 may be a part of the audio device 101. In alternative embodiment, the text-to-speech device 107 may be positioned externally to the audio device 101 as shown in Fig. 2. It will be appreciated, however, that additional components may be incorporated as required. The audio device 101 including the text-to-speech device 107 may be communicatively coupled to the display unit 103, and the controller 105 via wired or wireless means. In an exemplary embodiment, the audio device 101 may be coupled to these components / units through a physical communication interface, such as an auxiliary (AUX) connector. In an embodiment, the audio device 101 may comprise a speaker system configured to convey the operational status or current state of a printing press device or machine to operators or personnel within a plant or a factory.

[0029] Further, the display unit 103 may be configured to visually present information related to the operational status of the printing press device or machine. In one embodiment, the display unit 103 may comprise a graphical user interface (GUI) capable of displaying status indicators, such as error messages, operational parameters, or process updates. The display unit 103 may be implemented as a standalone device or integrated with the printing press machine.

[0030] The display unit 103 may comprise, but is not limited to, a touchscreen display, a Liquid Crystal Display (LCD) panel, a Light Emitting Diode (LED) display, or an e-ink screen. The display unit 103 may be communicatively coupled to the controller 105 via wired or wireless means to receive and display real-time data. In one embodiment, the display unit 103 may be configured to show a visual representation of audio feedback to be provided by the audio device 101, such as textual transcription or visual alerts, enabling operators to correlate audio and visual information for improved comprehension.

[0031] Furthermore, the display unit 103 may include customization capabilities, allowing operators to adjust display settings such as brightness, contrast, or the type of information displayed. In an embodiment, the display unit 103 may also feature an interactive interface, enabling operators to input commands, modify system parameters, or acknowledge alerts. Such interactions may further enhance the efficiency of monitoring and managing the printing press operations.

[0032] The controller 105, as illustrated in Fig. la, may be configured to receive status or indication from one or more components of printing press machine, and communicate or exchange information such as receiving input data and sending status, cumulative data and / or failure data output to the display unit 103. In an embodiment, the controller 105 may be implemented as a microcontroller, or an embedded processor capable of processing and executing instructions.

[0033] The controller 105 may be communicatively coupled to components of the printing press device or machine to receive operational data such as status updates, error logs, or performance metrics, or failure indications associated with different hardware components of the printing press machine or device. Based on the received data, the controller 105 may generate control signals or commands to drive the operation of the audio device 101, and display unit 103. For instance, in one embodiment, the controller 105 may trigger the audio device 101 via the display unit 103 to provide audible feedback or alerts while simultaneously instructing the display unit 103 to present corresponding visual information. In an embodiment, the controller 105 may be configured to transmit the operational data to the display unit 103. Upon receiving the operational data, the display unit 103 may generate an input signal and transmit the input signal to the audio device 101, enabling the audio device 101 to providing audible feedback.

[0034] In an embodiment, the controller 105 may include memory (not shown in Fig. la) to store predefined instructions, operational configurations, or recorded data. The memory may comprise volatile memory such as RAM or non-volatile memory such as flash storage. The controller 105 may also include a communication interface to support data exchange via wired or wireless protocols, such as Universal Serial Bus (USB), Bluetooth, Wireless Fidelity (Wi-Fi), or Ethernet.

[0035] The controller 105 may be further configured to process real-time inputs from the printing press machine and prioritize alerts or feedback based on predefined thresholds or conditions. For example, the controller 105 may escalate certain operational status alerts to both the audio device 101 and the display unit 103 for immediate attention. Additionally, the controller 105 may enable customization of operational settings, allowing operators to configure the type and format of feedback provided by the system.

[0036] In an alternate embodiment, the controller 105 may support integration with external systems or networked environments, enabling centralized monitoring and control of multiple printing pressdevices or machines within a facility. This integration may enhance operational efficiency and provide a unified platform for managing the printing press operations.

[0037] Further, the text-to-speech device 107 may be configured to convert textual information related to the operational status of the printing press device or machine into audible feedback. In an embodiment, the text-to-speech device 107 may receive textual data from the controller 105 via the display unit 103 and process it using speech synthesis algorithms to generate audio output.

[0038] In an embodiment, the text-to-speech device 107 may be implemented as a standalone hardware module, an integrated component of the audio device 101, or as software executing on a computing platform. The text-to-speech device 107 may support multiple languages, accents, and voice modulation options to provide customized and intelligible audible feedback for operators in diverse environments.

[0039] In an embodiment, the text-to-speech device 107 may be communicatively coupled to the audio device 101 via a wired interface, such as USB or serial communication, or a wireless interface, such as Bluetooth or Wi-Fi. The text-to-speech device 107 may process real-time inputs from the controller 105 received via the display unit 103 to provide immediate and contextually relevant audio feedback. Furthermore, the text-to-speech device 107 may include memory (not shown in Fig. la) to store pre-defined audio templates or textual data for commonly used alerts or messages.

[0040] In an alternate embodiment, the text-to-speech device 107 may operate in conjunction with the display unit 103 and audio device 101 to synchronize visual and audible feedback. For instance, the text-to-speech device 107 may vocalize error messages or operational instructions displayed on the display unit 103, thereby enhancing the clarity and effectiveness of communication within the operational environment.

[0041] In some embodiments, the text-to-speech device 107 may be further configured to adapt the tone, pitch, or speed of the audible feedback based on the nature of the message. For example, operational status alerts may be conveyed with an urgent tone, while informational messages may be delivered in a neutral tone, ensuring effective communication of the operational status to the operators.

[0042] The audio device 101 may comprise, but not limited to, a processor 109 and a memory 111. The processor 109 may be coupled to the memory 111. As used herein, the term ‘processor’ may referto an Application Specific Integrated Circuit (ASIC), an electronic circuit, a hardware processor (shared, dedicated, or group) and the memory 111 that execute one or more software or firmware programs, a combinational logic circuit, and / or other suitable components that provide the described functionality. In some embodiments, the processor 109 may be configured to perform one or more functions of the audio device 101 for transmitting operational data or status to the operators.

[0043] In a non-limiting embodiment, the memory 111 may be an external memory chip or an inbuilt EEPROM memory, within the audio device 101. In an embodiment, the memory 111 may be a computer-readable medium known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and / or synchronous dynamic random-access memory (SDRAM) and / or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes. In some implementations, the input data or any other data may be stored within the memory 111 in the form of various data structures. Additionally, the data may be organized using data models, such as relational or hierarchical data models. The other data may include various temporary data and files generated by the processor 109. However, the description should not be taken into limiting sense.

[0044] Fig. lb shows an exemplary environment for processing an audio signal to control an operation of a textile printing press device, in accordance with another embodiment of the present disclosure.

[0045] The exemplary environment 100b comprises an audio device (also, referred as audio output device) 101, a display unit (also, referred as touch screen display unit) 103, a controller (also, referred as main logic controller device) 105, at least one microphone 113 (also, referred as a microphone), and a PLC 115. The functionalities of the audio device 101, the display unit 103, and the controller 105 illustrated in Fig. lb correspond to those previously described with reference to Fig. la. To avoid repetition, such overlapping functionalities are not restated herein. Fig. lb further depicts additional functionalities of the audio device 101, the display unit 103, and the controller 105, which are described below. The controller 105 is communicatively connected to the at least one microphone 113. In one embodiment, the at least one microphone 113 is wirelessly connected to the controller 105 using, but not limited to, short-range protocols like Bluetooth or RF. The PLC 115 is communicatively connected to the controller 105 and the audio device 101. In one embodiment, the PLC 115 may be a part of the textile printing press device (not shown in Fig. lb). In one embodiment, the audio device 101, the display unit 103, the controller 105, at least one microphone 113, and the PLC 115collectively form a system for processing an audio signal to control an operation of a textile printing press device.

[0046] The at least one microphone 113 may be at least one directional microphone array configured with an acoustic beamforming technology. The beamforming focuses on an audio input signal signal from a desired direction while attenuating unwanted sounds from other directions. This improves the signal-to-noise ratio (SNR), which is advantageous in operational environments exhibiting spectral noise patterns generated by one or more other textile printing press devices. Further, by isolating the operator’s voice, beamforming ensures clearer audio capture. The at least one directional microphone array can determine the direction of arrival (DoA) of sound waves. This enables to track and respond to a specific operator. In one embodiment, the at least one microphone 113 is integrated within the audio device 101. In another embodiment, the at least one microphone 113 is positioned external to the audio device 101 and operatively coupled thereto (not shown in Fig. lb).

[0047] Hereinafter, the operation or method for processing an audio signal to control an operation of a textile printing press device is explained with reference to Fig. lb.

[0048] When an operator wants to operate a textile printing press device, the operator may speak via the microphone 113 to provide an audio input signal. The controller 105 receives the audio input signal from the operator via the microphone 113. The audio input signal comprises at least one machine-specific instruction. The at least one machine-specific instruction may also be referred as wake-word or wake-up word. For example, the audio input signal may include a machine-specific instruction or wake-up word such as “Hey Machine Name”. These machine-specific instructions included functions or command word, for example, "Set four strokes in head 5," "auto mode," "head 1 stop front”, and the like. The operator access is strictly controlled by a mandatory wake-up word (e.g., "Hey 'Machine Name'") followed by functions or command words, which are limited in scope to avoid access to functions that could cause personnel hazard. Thereafter, the controller 105 along with the microphone 113 filters the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices present in the vicinity of the textile printing press device. For example, the spectral noise patterns characteristic of one or more other textile printing press devices could be, but not limited to, the continuous, high-decibel hum of conveyor systems, drying units, and the operation of the print heads. The controller 105 uses digital signal processing (DSP) algorithms, which are known in the art, specifically trained to identify and subtract the spectralnoise paterns characteristic of one or more other textile printing press devices. Subsequently, the controller 105 determines an authenticity of the audio input signal using a trained NLP model. In one embodiment, the NLP model may be a part of the controller 105. In detail, the controller 105 detecting the at least one machine-specific instruction in the audio input signal. Thereafter, the controller 105 evaluates the at least one machine-specific instruction against pre-stored audio instructions using the trained NLP model. The NLP model uses an automatic speech recognition (ASR) model, which utilizes its training data i.e., pre-stored audio instructions derived from thousands of hours of operator data. The trained NLP model including the ASR model is configured to recognize at least one of languages, operator accents such as, but not limited to, vocal cadence variations and regional accents, and technical commands associated to the textile printing press device. The trained NLP model including the ASR model was trained on thousands of hours of speech data collected from operators across various international sites, ensuring high recognition accuracy across various languages combined with accent or vocal cadence. Subsequently, the controller 105 calculates a first confidence score of the at least one machine-specific instruction based on the evaluation. For example, if the signal-to-noise ratio associated with the at least one machine-specific instruction in terms of at least one of languages, operator accents, and technical commands is too low or ambiguous, the controller 105 discards the at least one machine-specific instruction as "unintentional speech," and assigns a low confidence score. Analogously, if the signal-to-noise ratio associated with the at least one machinespecific instruction in terms of at least one of languages, operator accents, and technical commands is high or not ambiguous, the controller 105 considers the at least one machine-specific instruction as "intentional speech," and assigns a high confidence score, ensuring only high confidence the audio input signal proceeds to the next phase. The controller 105 determines the authenticity of the at least one machine-specific instruction based on the first confidence score. In next phase, the controller 105 splits the at least one machine-specific instruction into at least one token when the first confidence score is above a first predetermined threshold value. For instance, the controller 105 determines the at least one machine-specific instruction to be authentic when the first confidence score is above the first predetermined threshold value. Analogously, the controller 105 determines the at least one machine-specific instruction to be not authentic when the first confidence score is less than or equal to the first predetermined threshold value. The first predetermined threshold value may be set by the operator of the textile printing press device. For example, the trained NLP model breaks / splits the at least one machine-specific instruction (also, referred as strings) into at least one token. The machinespecific instruction / command "Head 1 stop front" is tokenized into [NODE: HEAD l], [ACTION:STOP], and [POSITION: FRONT], Thereafter, the controller 105 maps the at least one token with predefined textile printing commands using, but not limited to, a finite state grammar technique. For example, the controller 105 utilizes a finite state grammar (FSG). This method recognizes 300+ predefined textile printing commands. If the token falls outside this "constrained grammar," the token is immediately flagged as a Null Command by this method. Subsequently, the controller 105 calculates a second confidence score of the at least one token based on the mapping. For example, the controller 105 calculates a second confidence score ($0.0$ to $1.0$) for the entire string or the at least one machine-specific instruction. If the second confidence score is below a second predetermined threshold value (e.g., $0.85$), the controller 105 requires a "Repeat Command" rather than risking an incorrect instruction to the PLC 115. The controller 105 determines the authenticity of the at least one token based on the second confidence score. A rigorous confidence scoring mechanism implemented within the NLP model, significantly reduces false commands generated from environmental noise or unintentional speech.

[0049] Lastly, the controller 105 transmitting the audio input signal to the PLC 115 of the textile printing press device for controlling the operation of the textile printing press device based on the determination. In detail, the controller 105 constructs a data frame comprising a header, the at least one token, and a cyclic redundancy check code when the second confidence score is above the second predetermined threshold value. The data frame is constructed when the second confidence score is above the second predetermined threshold value. The data frame is not constructed when the second confidence score is less than or equal to the second predetermined threshold value. The second predetermined threshold value may be set by the operator of the textile printing press device. For example, the at least one token is packaged into a data frame. This frame includes the header, the at least one token as command code (in hexadecimal), and a cyclic redundancy check (CRC) to ensure no data corruption occurs during transmission. Thereafter, the controller 105 establishes a dedicated socket connection with the PLC 115 of the textile printing press device. For example, the NVIDIA® board 201 acts as a TCP Client, establishing a dedicated socket connection to the PLC's 115 IP address. By using the TCP / IP protocol, the controller 105 ensures "Ordered Delivery" and "Retransmission" in case of network packet loss. The controller 105 transmits the data frame to the PLC 115 using the dedicated socket connection. This communication established using the TCP / IP protocol is reliable, has low-latency, and has robust data transfer across the industrial network.

[0050] The PLC 115 receives the data frame from the controller 105 using the dedicated socket connection. The PLC 115 converts the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device. In detail, the PLC 115 extracts the at least one token received in the data frame. The PLC 115 maps the at least one token in data frame with the at least one machine-readable control instruction stored in the PLC. For example, the PLC 115 maps the at least one token in data frame directly into specific Memory Addresses or Register Offsets within the PLC 115. Instead of "Head 1 Stop," the PLC 115 sends a write-command to a specific bit (e.g., Write 1 to Register 40001). The PLC 115 determines an operational status or current state of the textile printing press device. The PLC 115 controls the operation of the textile printing press device using the at least one machine-readable control instruction based on the operational status of the textile printing press device. The PLC 115 transmits the least one machine-readable control instruction to the display unit 103 via the controller 105 to display the operational status of the textile printing press device. For example, the PLC 115 simultaneously broadcast to the display unit 103 to update the textile printing press device state / status in real-time, ensuring the visual interface matches the internal logic state of the PLC 115. In an embodiment, the PLC 115 may include command interlocks and operational logic to ensure equipment safety and prevent operational conflicts. The PLC 115 may employ software-based interlocks that restrict or permit command execution depending on the current operational state of the textile printing press device.

[0051] Manual and Setup Commands: Commands including Auto Mode Selection, Manual Mode Selection, Head Enable, and Head Stop Selection are interlocked to avoid interference with automated sequences. Execution of these commands is permitted only when the textile printing press device is not engaged in an active Auto Cycle. If the textile printing press device is mid-cycle, such commands are automatically ignored to prevent mechanical damage or interruption of the process.

[0052] Auto Cycle Stop Command: The Stop Machine command is governed by permissive logic. This command is enabled exclusively while the machine is operating in an Auto Cycle. The logic ensures that the stop sequence is dedicated to terminating the active automated process, thereby maintaining operational integrity and controlled shutdown.

[0053] The audio device 101 obtains a signal associated with the operational status or current state of the textile printing press device from the display unit 103. Thereafter, the audio device 101 generates an audio output corresponding to the signal associated with the operational status of the textile printingpress device. The audio output comprises audible feedback for communicating the operational status associated with the textile printing press.

[0054] Fig. 2a shows an exemplary process flow for providing operational status by an audio device 101, in accordance with an embodiment of the present disclosure. As illustrated in step 1, the display unit 103 receives input data from an operator, which may include the selection of a specific function or feature. The input data is then transmitted to the controller 105 by the display unit 103 for processing. In steps 2 and 3, the controller 105 processes the real-time data associated to the selected function or feature, which includes the running status of the machine or failure indications from various hardware components.

[0055] Upon processing the real-time data, the controller 105 transmits the operational status or relevant data to the display unit 103 as shown in step 4. The display unit 103 then generates and displays a visual representation of the operational data, allowing the operator to review the current machine status. Concurrently, in one implementation, as shown in step 5 and 6, the controller 105 may transmit the real-time data to the text-to-speech device 107, enabling the audio device 101 to generate audible feedback for the operator.

[0056] In another implementation, the display unit 103 transmits an input signal to the audio device 101, which emits the corresponding audible feedback based on the operational status or data of the printing press machine as shown in step 7. This coordinated process ensures that both visual and auditory cues are provided to the operator, enhancing awareness and facilitating prompt responses to changes in the machine's operational state.

[0057] In one embodiment, the audio device 101 plays a role in assisting the operator during the job setup phase by providing auditory feedback based on the function or feature selected through the display unit 103. Upon the operator selecting the specific function or feature via the display unit 103, the display unit 103 may process the selection and triggers the audio device 101 to generate a corresponding audio notification. This auditory feedback may be communicated to the operator and any personnel in the vicinity that a change or selection has been made. Thus, this ensures that the operator is informed of any operational modifications, such as adjustments to settings, mode transitions, or job configuration changes, which may otherwise be overlooked. Further, the audio device 101 may provide immediate and clear audio cues, which assist in enhancing communicationefficiency, particularly in noisy or large production environments. For instance, when the operator changes to an operating mode or selects a new job configuration, the display unit 103 may cause the audio device 101 to emit an audible announcement, thereby informing both the operator and any nearby personnel of the machine’s current operational status. This facilitates coordination and awareness, promoting a proactive work environment.

[0058] The audio device 101 may also serve as an essential alerting mechanism for notifying the operator and surrounding personnel of faults, malfunctions, or system failures that occur during machine operation. In an embodiment, the controller 105, in conjunction with the display unit 103, continuously may monitor the operational status or current state of the printing press machine. Upon detecting any operational anomaly, such as breakdowns, system errors, or human errors, the controller 105 may issue a command to the audio device 101 via the display unit 103 to emit an alarm or status indication. The audio device 101 may provide immediate auditory alerts, ensuring that the operator and nearby personnel are promptly informed of the issue, allowing for quick intervention. For example, if a condition such as low air pressure is detected, the controller 105 may trigger the audio device 101 to issue an alarm. This audible warning is synchronized with the visual indication on the display unit 103, ensuring that the operator receives timely alerts regardless of whether they are directly observing the screen. This dual-alert system enhances response times, particularly for issues requiring immediate attention, thus ensuring the efficient and safe operation of the machine.

[0059] In addition to status alerts and operator assistance, the audio device 101 may be configured to convey performance data of the printing press device or machine to the operator. The controller 105 may continuously collect and processes various machine performance metrics, such as the total number of operations completed, the current printing speed, elapsed time since the last cycle completion, machine idle time, and machine downtime. Once the controller 105 processes these data points, the controller 105 may transmit commands to the audio device 101 via the display unit 103 to provide the relevant information to the operator in the form of auditory feedback. For instance, if the machine has been idle for an extended period, the controller 105 may trigger the audio device 101 via the display unit 103 to notify the operator of the idle status, helping the operator to identify underutilized machine time. As described earlier, the controller 105 may provide real-time inputs to the text-to-speech device 107 of the audio device 101 for processing the inputs using speech synthesis algorithms to generate audio output. The audio output is further provided to the audio device 101 to provide immediate and contextually relevant audio feedback.

[0060] Additionally, the audio device 101 may announce job completions or production milestones, which assist the operator in tracking progress and making informed decisions. The integration of realtime performance updates through auditory notifications ensures that operators can manage the printing process efficiently, enabling them to adjust machine operations as needed for optimal performance.

[0061] In another embodiment, the audio assistance may be implemented by utilizing a Nvidia® board 201 for the transfer of audio messages to the audio device 101 as shown in Fig. 2b. In one embodiment, the Nvidia® board 201 may be a part of the controller 105. In this configuration, prerecorded audio files may be stored on the Nvidia® board 201, which operates independently to facilitate communication with the controller 105 via a Transmission Control Protocol (TCP) / Internet Protocol (IP). In some embodiments, a human-machine interface (HMI) may be excluded from use in the generation or management of voice-related functionalities in this approach. However, the description should not be taken into limiting sense.

[0062] In another embodiment, the audio assistance may be implemented using a Raspberry Pi® board 203 to facilitate the transfer of audio messages to the audio device 101 as shown in Fig. 2c. In one embodiment, the Raspberry Pi® board 203 may be a part of the controller 105. In this configuration, the Raspberry Pi® board operates independently to establish communication with the controller 105 via the TCP / IP protocol. Notably, the HMI may be excluded from the process and may not be utilized for generating or managing voice-related functionalities. However, the description should not be taken into limiting sense.

[0063] In yet another embodiment, the audio assistance may be implemented using a customized board 205 to facilitate the transfer of audio messages to the audio device 101 as shown in Fig. 2d. In one embodiment, the customized board 205 may be a part of the controller 105. In this configuration, the customized board 205 operates independently to establish communication with the controller 105 via the TCP / IP protocol. Notably, the HMI may be excluded from the process and may not be utilized for generating or managing voice-related functionalities. However, the description should not be taken into limiting sense.

[0064] Fig. 3 shows a method flowchart for providing operational status by an audio device, in accordance with an embodiment of the present disclosure. The method 300 may be described in the general context of computer executable instructions. Generally, computer executable instructions may include routines, programs, objects, components, data structures, procedures, units, and functions, which perform specific functions or implement specific abstract data types.

[0065] The order in which the method 300 is described is not intended to be construed as a limitation, and any number of the described method blocks may be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described. Further, it may be noted that the method 300 may be performed by the audio device 101 as shown in Fig. la and Fig. lb. The description of Fig. 3 is provided with reference to Figs, la-b, to 2a-d.

[0066] At block 301, the method 300 comprises obtaining, by the audio device 101, an input signal associated with operational status or current state of a textile printing press device. The input signal may be obtained from the display unit 103.

[0067] Further, the method 300 at block 303 comprises generating, by the audio device 101, an audio output corresponding to the input signal. The audio output may comprise audible feedback for communicating the operational status associated with the printing press device. The operational status or current state may include critical operational status.

[0068] Fig. 4a shows a detailed block diagram of a controller, in accordance with an embodiment of the present disclosure.

[0069] The controller 105 may include an Input-Output (I-O) interface 401, a processor 403, data 411 and one or more modules (also, referred as modules) 421, which are described herein in detail. In the embodiment, the data 411 may be stored within a memory 405.

[0070] The 1-0 interface 401 is configured to receive an audio input signal from an operator via the microphone 113 and transmit the audio input signal to the PLC 115 of the textile printing press device based on the determination of the authenticity of the audio input signal. The 1-0 interface 401 employs communication protocols / methods such as, without limitation, audio, analog, digital, monoaural, Radio Corporation of America (RCA) connector, stereo, IEEE®- 1394 high speed serial bus, serialbus, Universal Serial Bus (USB), infrared, Personal System / 2 (PS / 2) port, Bayonet Neill-Concelman (BNC) connector, coaxial, component, composite, Digital Visual Interface (DVI), High-Definition Multimedia Interface (HDMI®), Radio Frequency (RF) antennas, S-Video, Video Graphics Array (VGA), IEEE® 802.11b / g / n / x, Bluetooth, cellular e.g., Code-Division Multiple Access (CDMA), High-Speed Packet Access (HSPA+), Global System for Mobile communications (GSM®), Long-Term Evolution (LIE®), Worldwide interoperability for Microwave access (WiMax®), or the like.

[0071] The audio instructions and predefined textile printing commands are stored in the memory 405. The memory 405 is communicatively coupled to the processor 403 of the controller 105. The memory 405, also, stores processor-executable instructions which may cause the processor 403 to execute the instructions for processing an audio signal to control an operation of a textile printing press device. The memory 405 includes, without limitation, memory drives, removable disc drives, etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc.

[0072] The processor 403 includes at least one data processor for processing an audio signal to control an operation of a textile printing press device. The processor 403 may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.

[0073] In the embodiment, the data 411 may be stored within the memory 405. The data 411 may include, for example, audio data 413, command data 415, and miscellaneous data 417.

[0074] The audio data 413 may include audio instructions. The audio instructions are pre-stored in the audio data 413. The command data 415 may include predefined textile printing commands. The predefined textile printing commands are pre-stored in the command data 415. The miscellaneous data 417 may store data, including temporary data and temporary files, generated by modules 421 for performing various functions of the controller 105.

[0075] In an embodiment, the data 411 in the memory 405 are processed by the one or more modules 421 present within the memory 405 of the controller 105. In the embodiment, the one or more modules 421 may be implemented as dedicated hardware units. As used herein, the term module refers to anApplication Specific Integrated Circuit (ASIC), an electronic circuit, a Field-Programmable Gate Arrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and / or other suitable components that provide the described functionality. In some implementations, the one or more modules 421 may be communicatively coupled to the processor 403 for performing one or more functions of the controller 105. The modules 421 when configured with the functionality defined in the present disclosure will result in a novel hardware.

[0076] In one implementation, the one or more modules 421 may include, but are not limited to, a transceiver 423, a filter module 425, and an authenticator module 427. The one or more modules 421 may, also, include miscellaneous modules 429 to perform various miscellaneous functionalities of the controller 105.

[0077] Transceiver 423: The transceiver 423 receives an audio input signal from an operator via the microphone 113. The audio input signal comprises at least one machine-specific instruction. The transceiver 423 transmits the audio input signal to the PLC 115 of the textile printing press device for controlling the operation of the textile printing press device based on the determination of the authenticity of the audio input signal. In detail, the transceiver 423 constructs a data frame. The data frame comprises a header, the at least one token, and a cyclic redundancy check code. The data frame is constructed when the second confidence score is above a second predetermined threshold value. The data frame is not constructed when the second confidence score is less than or equal to the second predetermined threshold value. Thereafter, the transceiver 423 establishes a dedicated socket connection with the PLC 115 of the textile printing press device. Subsequently, the transceiver 423 transmits the data frame to the PLC 115 using the dedicated socket connection.

[0078] Filter module 425: The filter module 425 filters the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices.

[0079] Authenticator module 427: The authenticator module 427 determines an authenticity of the audio input signal using a trained NLP model. In detail, the authenticator module 427 detects the at least one machine-specific instruction in the audio input signal. Thereafter, the authenticator module 427 evaluates the at least one machine-specific instruction against the pre-stored audio instructions using the trained NLP model. Subsequently, the authenticator module 427 calculates a first confidence score of the at least one machine-specific instruction based on the evaluation. Lastly, the authenticatormodule 427 determines the authenticity of the at least one machine-specific instruction based on the first confidence score. For instance, the authenticator module 427 determines the at least one machinespecific instruction to be authentic when the first confidence score is above a first predetermined threshold value. Analogously, the authenticator module 427 determines the at least one machinespecific instruction to be not authentic when the first confidence score is less than or equal to the first predetermined threshold value.

[0080] The authenticator module 427 splits the at least one machine-specific instruction into at least one token when the first confidence score is above the first predetermined threshold value. Thereafter, the authenticator module 427 maps the at least one token with predefined textile printing commands using, but not limited to, a finite state grammar technique / method. Subsequently, the authenticator module 427 calculates a second confidence score of the at least one token based on the mapping. Lastly, the authenticator module 427 determines the authenticity of the at least one token based on the second confidence score. For instance, the authenticator module 427 determines the at least one token to be authentic when the second confidence score is above the second predetermined threshold value. Analogously, the authenticator module 427 determines the at least one token to be not authentic when the second confidence score is less than or equal to the second predetermined threshold value.

[0081] In one embodiment, the NLP model may be a part of the authenticator module 427 of the controller 105.

[0082] Fig. 4b shows a detailed block diagram of a programmable logic controller, in accordance with an embodiment of the present disclosure.

[0083] The PLC 115 may include an 1-0 interface 451, a processor 453, data 461 and one or more modules (also, referred as modules) 471, which are described herein in detail. In the embodiment, the data 461 may be stored within a memory 455.

[0084] The 1-0 interface 451 is configured to receive an audio input signal from the controller 105 and transmit the least one machine-readable control instruction to the display unit 103 via the controller 105 to display the operational status of the textile printing press device. The 1-0 interface 451 employs communication protocols / methods such as, without limitation, audio, analog, digital, monoaural, Radio Corporation of America (RCA) connector, stereo, IEEE®- 1394 high speed serialbus, serial bus, Universal Serial Bus (USB), infrared, Personal System / 2 (PS / 2) port, Bayonet Neill-Concelman (BNC) connector, coaxial, component, composite, Digital Visual Interface (DVI), High-Definition Multimedia Interface (HDMI®), Radio Frequency (RF) antennas, S-Video, Video Graphics Array (VGA), IEEE® 802.11b / g / n / x, Bluetooth, cellular e.g., Code-Division Multiple Access (CDMA), High-Speed Packet Access (HSPA+), Global System for Mobile communications (GSM®), Long-Term Evolution (LEE®), Worldwide interoperability for Microwave access (WiMax®), or the like.

[0085] The machine-readable control instructions are stored in the memory 455. The memory 455 is communicatively coupled to the processor 453 of the PLC 115. The memory 455, also, stores processor-executable instructions which may cause the processor 453 to execute the instructions for processing the audio signal to control an operation of a textile printing press device. The memory 455 includes, without limitation, memory drives, removable disc drives, etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc.

[0086] The processor 453 includes at least one data processor for processing the audio signal to control an operation of a textile printing press device. The processor 453 may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.

[0087] In the embodiment, the data 461 may be stored within the memory 455. The data 461 may include, for example, instruction data 463, and miscellaneous data 465.

[0088] The instruction data 463 may include machine-readable control instructions. The machine-readable control instructions are pre-stored in the instruction data 463. The miscellaneous data 465 may store data, including temporary data and temporary files, generated by modules 471 for performing various functions of the PLC 115.

[0089] In an embodiment, the data 461 in the memory 455 are processed by the one or more modules 471 present within the memory 455 of the PLC 115. In the embodiment, the one or more modules 471 may be implemented as dedicated hardware units. As used herein, the term module refers to an Application Specific Integrated Circuit (ASIC), an electronic circuit, a Field-Programmable GateArrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and / or other suitable components that provide the described functionality. In some implementations, the one or more modules 461 may be communicatively coupled to the processor 453 for performing one or more functions of the PLC 115. The modules 471 when configured with the functionality defined in the present disclosure will result in a novel hardware.

[0090] In one implementation, the one or more modules 471 may include, but are not limited to, a transceiver 473, a mapping module 475, and a control module 477. The one or more modules 471 may, also, include miscellaneous modules 479 to perform various miscellaneous functionalities of the PLC 115.

[0091] Transceiver 473: The transceiver 473 receives the audio input signal from the controller 105 for controlling the operation of the textile printing press device based on the determination of the authenticity of the audio input signal. The transceiver 473 transmits the least one machine-readable control instruction to the display unit 103 via the controller 105 to display the operational status of the textile printing press device.

[0092] Mapping module 475: The mapping module 475 converts the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device. In detail, the mapping module 475 extracts the at least one token received in the data frame from the controller 105. Thereafter, the mapping module 475 maps the at least one token in data frame with the at least one machine-readable control instruction stored in the PLC 115. Subsequently, the mapping module 475 determines an operational status or current state of the textile printing press device.

[0093] Control module 477: The control module 477 controls the operation of the textile printing press device using the at least one machine-readable control instruction based on the operational status or current state of the textile printing press device. In an embodiment, the control module 477 may control command interlocks and operational logic to ensure equipment safety and prevent operational conflicts. The The control module 477 may employ software-based interlocks that restrict or permit command execution depending on the current operational state of the textile printing press device.

[0094] Manual and Setup Commands: Commands including Auto Mode Selection, Manual Mode Selection, Head Enable, and Head Stop Selection are interlocked to avoid interference with automatedsequences. Execution of these commands is permitted only when the textile printing press device is not engaged in an active Auto Cycle. If the textile printing press device is mid-cycle, such commands are automatically ignored by the control module 477 to prevent mechanical damage or interruption of the process.

[0095] Auto Cycle Stop Command: The Stop Machine command is governed by permissive logic. This command is enabled exclusively by the control module 477 while the machine is operating in an Auto Cycle. The logic ensures that the stop sequence is dedicated to terminating the active automated process, thereby maintaining operational integrity and controlled shutdown.

[0096] Fig. 5 illustrates a flowchart showing a method for processing an audio signal to control an operation of a textile printing press device, in accordance with an embodiment of the present disclosure.

[0097] As illustrated in Fig. 5, the method 500 includes one or more blocks for processing an audio signal to control an operation of a textile printing press device in accordance with some embodiments of the present disclosure. The method 500 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions or implement particular abstract data types.

[0098] The order in which the method 500 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

[0099] At block 501, the transceiver 423 of the controller 105 receives an audio input signal from an operator via the microphone 113. The audio input signal comprises at least one machine-specific instruction.

[0100] At block 503, the filter module 425 of the controller 105 filters the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices.

[0101] At block 505, the authenticator module 427 of the controller 105 determines an authenticity of the audio input signal using a trained NLP model.

[0102] At block 507, the transceiver 423 of the controller 105 transmits the audio input signal to the PLC 115 of the textile printing press device for controlling the operation of the textile printing press device based on the determination.

[0103] At block 509, the mapping module 475 of the PLC 115 converts the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device.

[0104] Some of the advantages of the present disclosure are presented below:• Improved Communication: The present disclosure provides clear, real-time auditory feedback, ensuring that operators are consistently informed of the machine's status. This reduces the likelihood of errors and missed warnings, enhancing overall communication within the operational environment.• Increased Efficiency: By delivering audible notifications alongside visual cues, the present disclosure allows the operator to multitask more effectively, improving workflow and productivity without compromising attention to critical machine statuses.• Enhanced Awareness: The audio feedback, including alarms and status indications, ensures that operators and nearby personnel are immediately notified of any operational issues, promoting a heightened state of awareness and fostering a more responsive and proactive work environment.• Better Data Awareness: The present disclosure facilitates real-time access to key machine performance metrics, empowering operators to make well-informed decisions that optimize the efficiency and effectiveness of the printing process.• Improved safety: The present disclosure reduces or eliminates the need for manual intervention by operators, particularly in noisy factory environments and in the presence of large-scale printing press machinery. By minimizing reliance on direct operator involvement, the present disclosure enhances overall safety, mitigates conditions that may impair communication, and lowers the risk of accidents or operator injury.

[0105] Some of the clauses are mentioned below.[1]: A method for processing an audio signal to control an operation of a textile printing press device, the method comprising:receiving an audio input signal from an operator via a microphone, wherein the audio input signal comprises at least one machine-specific instruction;filtering the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices;determining an authenticity of the audio input signal using a trained natural language processing (NLP) model; andtransmitting the audio input signal to a programmable logic controller (PLC) of the textile printing press device for controlling the operation of the textile printing press device based on the determination.[2]: The method as described in [1], further comprises:converting the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device.[3]: The method as described in [1], wherein determining the authenticity of the audio input signal using the trained NLP model comprises:detecting the at least one machine-specific instruction in the audio input signal; evaluating the at least one machine-specific instruction against pre-stored audio instructions using the trained NLP model;calculating a first confidence score of the at least one machine-specific instruction based on the evaluation; anddetermining the authenticity of the at least one machine-specific instruction based on the first confidence score.[4]: The method as described in [3], further comprises:splitting the at least one machine-specific instruction into at least one token when the first confidence score is above a first predetermined threshold value;mapping the at least one token with predefined textile printing commands using a finite state grammar technique;calculating a second confidence score of the at least one token based on the mapping; and determining the authenticity of the at least one token based on the second confidence score.[5]: The method as described in [1] or [4], wherein transmitting the audio input signal to the PLC of the textile printing press device for controlling the operation of the textile printing press device based on the determination comprises:constructing a data frame comprising a header, the at least one token, and a cyclic redundancy check code when the second confidence score is above a second predetermined threshold value; establishing a dedicated socket connection with the PLC of the textile printing press device; andtransmitting the data frame to the PLC using the dedicated socket connection.[6]: The method as described in [2], wherein converting the audio input signal into the at least one machine-readable control instruction to control the operation of the textile printing press device comprises:extracting the at least one token received in the data frame;mapping the at least one token in data frame with the at least one machine-readable control instruction stored in the PLC;determining an operational status of the textile printing press device;controlling the operation of the textile printing press device using the at least one machine-readable control instruction based on the operational status of the textile printing press device; and transmitting the least one machine-readable control instruction to a display unit via the controller to display the operational status of the textile printing press device.[7]: The method as described in [6], further comprising:obtaining a signal associated with the operational status of the textile printing press device from the display unit; andgenerating an audio output corresponding to the signal associated with the operational status of the textile printing press device,wherein the audio output comprises audible feedback for communicating the operational status associated with the textile printing press.[8]: The method as described in [1], wherein the audio input signal is received using at least one directional microphone array configured with an acoustic beamforming technology.[9]: The method as described in [1], wherein the trained NLP model is configured to recognize at least one of languages, operator accents, and technical commands associated to the textile printing press device.

[0010] : A system for processing an audio signal to control an operation of a textile printing press device, the system comprising:at least one directional microphone array with an acoustic beamforming technology configured to:receive an audio input signal from an operator via a microphone, wherein the audio input signal comprises at least one machine-specific instruction;a controller communicatively connected to the at least one directional microphone array, the controller is configured to:filter the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices;determine an authenticity of the audio input signal using a trained natural language processing (NLP) model; andtransmit the audio input signal to a programmable logic controller (PLC) of the textile printing press device for controlling the operation of the textile printing press device based on the determination.

[0011] : The system as described in

[0010] , further comprising:the PLC communicatively connected to the controller, the PLC is configured to:convert the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device.

[0012] : The system as described in

[0010] , wherein to determine the authenticity of the filtered audio input signal using the trained NLP model, the controller is configured to:detect the at least one machine-specific instruction in the audio input signal;evaluate the at least one machine-specific instruction against pre-stored audio instructions using the trained NLP model;calculate a first confidence score of the at least one machine-specific instruction based on the evaluation; anddetermine the authenticity of the at least one machine-specific instruction based on the first confidence score.

[0013] : The system as described in

[0012] , wherein the controller is further configured to:split the at least one machine-specific instruction into at least one token when the first confidence score is above a first predetermined threshold value;map the at least one token with predefined textile printing commands using a finite state grammar technique;calculate a second confidence score of the at least one token based on the mapping; and determine the authenticity of the at least one token based on the second confidence score.

[0014] : The system as described in

[0010] , wherein to transmit the audio input signal to the PLC of the textile printing press device for controlling the operation of the textile printing press device based on the determination, the controller is further configured to:construct a data frame comprising a header, the at least one token, and a cyclic redundancy check code when the second confidence score is above a second predetermined threshold value; establish a dedicated socket connection with the PLC of the textile printing press device; and transmit the data frame to the PLC using the dedicated socket connection.

[0015] : The system as described in

[0011] , wherein to convert the audio input signal into the at least one machine-readable control instruction to control the operation of the textile printing press device, the PLC is configured to:extract the at least one token received in the data frame;map the at least one token in data frame with the at least one machine-readable control instruction stored in the PLC;determine a current state of the textile printing press device;control the operation of the textile printing press device using the at least one machine-readable control instruction based on the current state of the textile printing press device; andtransmit the least one machine-readable control instruction to a display unit via the controller to display a current state of the textile printing press device.

[0016] : The system as described in

[0015] , further comprising:the audio device communicatively connected to the display unit, the audio device is configured to:obtain a signal associated with the operational status of the textile printing press device from the display unit; andgenerate an audio output corresponding to the signal associated with the operational status of the textile printing press device,wherein the audio output comprises audible feedback for communicating the operational status associated with the textile printing press.

[0017] : The system as described in

[0010] , wherein the trained NLP model is configured to recognize at least one of languages, operator accents, and technical commands associated to the textile printing press device.

[0106] With respect to the use of substantially any plural and singular terms herein, those having skill in the art can translate from the plural to the singular and from the singular to the plural as is appropriate to the context or application. The various singular or plural permutations may be expressly set forth herein for sake of clarity.

[0107] One or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which a software (program) readable by an information processing apparatus may be stored. The information processing apparatus includes a processor and a memory, and the processor executes a process of the software. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include RAM, ROM, volatile memory, non-volatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.

[0108] The described operations may be implemented as a method, a system, or an article of manufacture using at least one of standard programming and engineering techniques to produce software, firmware, hardware, or any combination thereof. The described operations may be implemented as code maintained in a “non-transitory computer readable medium”, where a processor may read and execute the code from the computer readable medium. The processor is at least one ofa microprocessor and a processor capable of processing and executing the queries. A non-transitory computer readable medium may include media such as magnetic storage medium (e.g., hard disk drives, floppy disks, tape, etc.), optical storage (CD ROMs, DVDs, optical disks, etc.), volatile and non-volatile memory devices (e g., EEPROMs, ROMs, PROMs, RAMs, DRAMs, SRAMs, Flash Memory, firmware, programmable logic, etc.), etc. Further, non-transitory computer-readable media include all computer-readable media except for a transitory. The code implementing the described operations may further be implemented in hardware logic (e.g., an integrated circuit chip, PGA, ASIC, etc.).

[0109] The terms "an embodiment", "embodiment", "embodiments", "the embodiment", "the embodiments", "one or more embodiments", "some embodiments", and "one embodiment" mean "one or more (but not all) embodiments of the invention(s)" unless expressly specified otherwise. The terms "including", "comprising", “having” and variations thereof mean "including but not limited to", unless expressly specified otherwise. The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise. The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.

[0110] A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention. When a single device or article is described herein, it will be readily apparent that more than one device / article (whether or not they cooperate) may be used in place of a single device / article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device / article may be used in place of the more than one device or article, or a different number of devices / articles may be used instead of the shown number of devices or programs. The functionality and / or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality / features. Thus, other embodiments of the invention need not include the device itself.

[0111] The illustrated operations of Figs. 3, and 5 show certain events occurring in a certain order. In alternative embodiments, certain operations may be performed in a different order, modified, or removed. Moreover, steps may be added to the above-described logic and still conform to the described embodiments. Further, operations described herein may occur sequentially or certainoperations may be processed in parallel. Yet further, operations may be performed by a single processing unit or by distributed processing units. Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims. While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope being indicated by the following claims.REFERRAL NUMERALS:

Claims

We claim:

1. A method for processing an audio signal to control an operation of a textile printing press device, the method comprising:receiving an audio input signal from an operator via a microphone, wherein the audio input signal comprises at least one machine-specific instruction;filtering the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices;determining an authenticity of the audio input signal using a trained natural language processing (NLP) model; andtransmitting the audio input signal to a programmable logic controller (PLC) of the textile printing press device for controlling the operation of the textile printing press device based on the determination.

2. The method as claimed in claim 1, further comprises:converting the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device.

3. The method as claimed in claim 1, wherein determining the authenticity of the audio input signal using the trained NLP model comprises:detecting the at least one machine-specific instruction in the audio input signal; evaluating the at least one machine-specific instruction against pre-stored audio instructions using the trained NLP model;calculating a first confidence score of the at least one machine-specific instruction based on the evaluation; anddetermining the authenticity of the at least one machine-specific instruction based on the first confidence score.

4. The method as claimed in claim 3, further comprises:splitting the at least one machine-specific instruction into at least one token when the first confidence score is above a first predetermined threshold value;mapping the at least one token with predefined textile printing commands using a finite state grammar technique;calculating a second confidence score of the at least one token based on the mapping; and determining the authenticity of the at least one token based on the second confidence score.

5. The method as claimed in claim 1 or 4, wherein transmitting the audio input signal to the PLC of the textile printing press device for controlling the operation of the textile printing press device based on the determination comprises:constructing a data frame comprising a header, the at least one token, and a cyclic redundancy check code when the second confidence score is above a second predetermined threshold value; establishing a dedicated socket connection with the PLC of the textile printing press device; andtransmitting the data frame to the PLC using the dedicated socket connection.

6. The method as claimed in claim 2, wherein converting the audio input signal into the at least one machine-readable control instruction to control the operation of the textile printing press device comprises:extracting the at least one token received in the data frame;mapping the at least one token in data frame with the at least one machine-readable control instruction stored in the PLC;determining an operational status of the textile printing press device;controlling the operation of the textile printing press device using the at least one machine-readable control instruction based on the operational status of the textile printing press device; and transmitting the least one machine-readable control instruction to a display unit via the controller to display the operational status of the textile printing press device.

7. The method as claimed in claim 6, further comprising:obtaining a signal associated with the operational status of the textile printing press device from the display unit; andgenerating an audio output corresponding to the signal associated with the operational status of the textile printing press device,wherein the audio output comprises audible feedback for communicating the operational status associated with the textile printing press.

8. The method as claimed in claim 1, wherein the audio input signal is received using at least one directional microphone array configured with an acoustic beamforming technology.

9. The method as claimed in claim 1, wherein the trained NLP model is configured to recognize at least one of languages, operator accents, and technical commands associated to the textile printing press device.

10. A system for processing an audio signal to control an operation of a textile printing press device, the system comprising:at least one directional microphone array with an acoustic beamforming technology configured to:receive an audio input signal from an operator via a microphone, wherein the audio input signal comprises at least one machine-specific instruction;a controller communicatively connected to the at least one directional microphone array, the controller is configured to:filter the audio input signal to eliminate spectral noise patterns characteristic of one or more other textile printing press devices;determine an authenticity of the audio input signal using a trained natural language processing (NLP) model; andtransmit the audio input signal to a programmable logic controller (PLC) of the textile printing press device for controlling the operation of the textile printing press device based on the determination.

11. The system as claimed in claim 10, further comprising:the PLC communicatively connected to the controller, the PLC is configured to: convert the audio input signal into at least one machine-readable control instruction to control the operation of the textile printing press device.

12. The system as claimed in claim 10, wherein to determine the authenticity of the filtered audio input signal using the trained NLP model, the controller is configured to:detect the at least one machine-specific instruction in the audio input signal;evaluate the at least one machine-specific instruction against pre-stored audio instructions using the trained NLP model;calculate a first confidence score of the at least one machine-specific instruction based on the evaluation; anddetermine the authenticity of the at least one machine-specific instruction based on the first confidence score.

13. The system as claimed in claim 12, wherein the controller is further configured to:split the at least one machine-specific instruction into at least one token when the first confidence score is above a first predetermined threshold value;map the at least one token with predefined textile printing commands using a finite state grammar technique;calculate a second confidence score of the at least one token based on the mapping; and determine the authenticity of the at least one token based on the second confidence score.

14. The system as claimed in claim 10, wherein to transmit the audio input signal to the PLC of the textile printing press device for controlling the operation of the textile printing press device based on the determination, the controller is further configured to:construct a data frame comprising a header, the at least one token, and a cyclic redundancy check code when the second confidence score is above a second predetermined threshold value; establish a dedicated socket connection with the PLC of the textile printing press device; and transmit the data frame to the PLC using the dedicated socket connection.

15. The system as claimed in claim 11 , wherein to convert the audio input signal into the at least one machine-readable control instruction to control the operation of the textile printing press device, the PLC is configured to:extract the at least one token received in the data frame;map the at least one token in data frame with the at least one machine-readable control instruction stored in the PLC;determine a current state of the textile printing press device;control the operation of the textile printing press device using the at least one machine-readable control instruction based on the current state of the textile printing press device; andtransmit the least one machine-readable control instruction to a display unit via the controller to display a current state of the textile printing press device.

16. The system as claimed in claim 15, further comprising:the audio device communicatively connected to the display unit, the audio device is configured to:obtain a signal associated with the operational status of the textile printing press device from the display unit; andgenerate an audio output corresponding to the signal associated with the operational status of the textile printing press device,wherein the audio output comprises audible feedback for communicating the operational status associated with the textile printing press.

17. The system as claimed in claim 10, wherein the trained NLP model is configured to recognize at least one of languages, operator accents, and technical commands associated to the textile printing press device.

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