140 results about "Vocal music" patented technology

The invention discloses a VEM-Token beat capture and alignment model construction method, which is a deepening innovation that a vocal music file is segmented into VEM-Token lexical elements by adopting music beats based on a VEM-Token vocal music emotion multi-modal model method. The core of the method is to establish a rhythm model, a rhythm capture model and a rhythm alignment model of a vocal music file, the rhythm model separates singing sound, accompaniment sound and emotional fluctuation from a sample vocal music file through multiple filters and captures a start point and an end point of a rhythm in a frequency spectrum format file, and the rhythm alignment model performs rhythm alignment on the vocal music file through a start point fine tuning model and an end point fine tuning model. And the user imitation file and the sample file are enabled to complete beat alignment. Models including a rhythm basic model, harmonic impact, joint learning, harmonic frequency layering, dynamic time warping and the like are adopted to capture rhythms, and models including the basic model, starting point fine tuning, terminal point fine tuning, whole-course alignment verification, a rhythm editor, rhythm free playing, repeated alignment, a communication interface protocol and the like are adopted to construct. Therefore, the method is suitable for accessing an Agent music agent and an AI music application.

The invention relates to the technical field of vocal music training evaluation, and discloses a vocal music training intelligent evaluation method and system based on voice analysis. The method comprises the following steps: firstly, acquiring vocal music training original data, and processing and aligning multi-modal data by using a transfer learning small sample completion method when the data is insufficient; constructing a pronunciation stability evaluation model and a comprehensive pronunciation performance evaluation model; constructing a pronunciation scene simulator for different vocal music styles; the evaluation parameters are analyzed through a Shapley value decomposition algorithm, and a lightweight index system is constructed; and establishing a training scheme optimization agent model by using Gaussian process regression and a Bayesian optimization algorithm. The system comprises a data acquisition and completion module, an evaluation module, a simulation module, an analysis module, an optimization module and the like. The vocal music training system can comprehensively and accurately evaluate vocal music training, adapts to various styles, optimizes a training scheme, and assists a singer to improve the singing level through real-time feedback and visual display.

The invention discloses a VEM-Token vocal music emotion multi-mode token song sound and accompaniment deep learning method, which is different from an existing method that information is segmented into textual token lexical elements by artificial intelligence and then recognition is carried out on the textual token lexical elements. The method comprises the following steps: performing frequency spectrum processing on a vocal music file, detecting rhythm, segmenting the vocal music file subjected to frequency spectrum processing into a VEM-Token sequence according to the vocal music rhythm, establishing a VEM coordinate system, a VEM function and a VEM library according to multiple modes such as lyrics, singing sound, accompaniment, singer emotion, accompaniment emotion, video and image, performing VEM-Token identification, separating a singing sound stream and an accompaniment stream, and determining the vocal music according to a vocal music expert. And performing multi-modal emotion scoring on the vocal music sample, obtaining a VEM parameter by adopting supervised learning and deep learning algorithms, and learning to obtain the multi-modal emotion of the vocal music sample. For other vocal music works, vocal music multi-mode emotions can be recognized, and a lyric score, a VEM-Token song sound score, a VEM-Token accompaniment score and a VEM-Token music score are output. AI systems including a common large model and the like are accessed, and a vocal music agent Agent capable of listening to the singing and identifying the music score is developed.

The invention provides a vocal music training vowel pronunciation quality evaluation method based on auditory and visual spatial-temporal feature fusion, and the method comprises the steps: collecting vowel pronunciation audio signals and corresponding videos of a singer, and constructing a multi-modal data set; generating a fractional order Mel spectrogram for the audio signal through short-time fractional order Fourier transform of an adaptive order; extracting time sequence features and spatial features of the fractional order Mel spectrogram, and fusing the time sequence features and the spatial features through a gating mechanism to generate audio spatio-temporal features; face visual features in the video are extracted and fused with the audio spatio-temporal features through a cross attention mechanism, and the cross attention mechanism is integrated with a periodic modeling network; the fused features are input into a classifier, a dynamic weight multi-mode cosine loss function training model is adopted, the dynamic weight multi-mode cosine loss function dynamically adjusts the sample weight through a confusion matrix, and the weight is increased for the samples with classification errors based on the historical frequency mistaken division times of the samples; and outputting a pronunciation quality evaluation result.

A VEM-Token emotion synchronization function hierarchical fusion method is different from a traditional NLP-Token method, an emotion synchronization function VEM-sync is innovated for the first time, the emotion synchronization function VEM-sync is synchronized with a VEM-Token sequence of music beats, multiple high-dimensional emotions are directly described by adopting mathematical languages, and therefore deviation of discretized natural language characters on description of a high-dimensional emotion analog quantity function is avoided, and the emotion synchronization effect is improved. The method comprises the steps of defining VEM-sync and synchronous content, defining rhythm attributes, emotion attributes and emotion functions, adopting one or combination of multi-layer weighted scanning, a recurrent neural network, a long and short-term memory network, a self-attention mechanism and an RAG network generated by retrieval enhancement, and performing hierarchical fusion calculation to output a time emotion function of a vocal music file. According to the phonetic function or the emotional function, the effects of emotional texts, emotional expressions, emotional languages and emotional multi-dimensional animations are directly driven by crossing discrete text tokens, a model context protocol (MCP) and a function calling function are supported, and copyright management and encryption and decryption or interfaces are provided.

The invention relates to the technical field of speech recognition, in particular to a sound model generation method and system for vocal music pronunciation training, and the method comprises the steps: collecting a preset number of sound signals of a trainer for different contents, and collecting a preset number of sound signals for each content; for any content and any modal component of any sound signal, obtaining each contrast component of the any modal component, and obtaining a feature difference array of the any modal component; obtaining a difference characteristic value between the any modal component and each contrast component thereof, obtaining an influence characteristic value and a reconstruction weight of the any modal component, and further obtaining each reconstructed sound signal; and obtaining a sound characteristic spectrum of each sound signal of the trainer, training a sound model, and evaluating the quality of new pronunciation of the trainer. The invention aims to improve the precision of the constructed vocal music pronunciation training sound model by improving the processing effect of the collected sound signals.

The invention discloses a music teaching method and system based on a vocal music live classroom, and relates to the technical field of music teaching, and the method comprises the steps: respectively collecting audio signals of a teacher end and a student end in the vocal music live classroom, carrying out the preprocessing, and generating frame-level acoustic feature vectors of teachers and students; based on frame-level acoustic feature vectors of teachers and students, generating a mapping feature vector, category probability and an adversarial sample set through mapping, domain discrimination and a CTC model, constructing a total loss function in combination with a loss function value of the model, and performing iterative optimization, gradient fixed-point rounding and feedback of model parameters; according to the invention, through constructing the total loss function, introducing the gradient inversion layer and the gradient fixed-point rounding mechanism, combining the three-state HMM state path and calculating the pronunciation quality logarithm score, the robustness and precision of student pronunciation evaluation in a vocal music live broadcast teaching scene are significantly improved, and thus a high-resolution teaching feedback basis is provided for teachers.

The construction method of the VEM-Token vocal emotion multi-modal magic modification model is different from the natural language processing model NLP-Token which interprets music through text. Instead, the VEM-Token sound-to-text innovation model comes with vocal emotion multi-modal information. The model captures and aligns the music tempo of sample songs and user learning songs, identifies various modalities of vocal emotion, divides the file into word units based on tempo, obtains VEM parameters through supervised learning and reinforcement learning, and decomposes songs into vocals, accompaniment, and emotion. The magic modification model provides a multi-modal magic modification method for imitating sample songs, including vocals, accompaniment, emotion overtones, emotion fluctuations, learning to sing, voice cloning, lyrics, pitch calibration, ornaments, tempo length, rhythm speed, tempo strength, freedom, and multiple sample magic modification. It also provides member management, mobile and PC application systems, dedicated support hardware, and communication protocols including MIDI, making it easy to access popular AI large models, reducing model hallucinations, and forming AI vocal agents and AI karaoke.

Disclosed are systems, methods, and devices, that overcome timing and self-expression limitations experienced by vocalists when using prerecorded vocal backing tracks to enhance live performances. The disclosed system, devices, and methods, dynamically synchronizes prerecorded vocal backing tracks with a live vocal stream by extracting vocal elements, such as phonemes, vector embeddings, or vocal audio spectra, from the live vocal performance in real-time. These extracted vocal elements are matched against corresponding timestamped vocal elements previously derived from the prerecorded vocal backing track, enabling precise real-time adjustment and alignment of the backing track timing to the live performance. Additionally, the system enhances expressive performance by identifying prosody factors, such as pitch, vibrato, accent, stress, dynamics, and level, in the live vocal performance, and dynamically adjusting corresponding prerecorded prosody factors within predefined ranges. This maintains naturalness and spontaneity in the vocalist's live performance, overcoming traditional limitations associated with prerecorded vocal backing tracks.

The invention provides a sounding position determination method and device and a vocal music practice system. The method comprises the following steps: acquiring a voice signal and a physiological signal of a sounding person; performing sound source positioning on the voice signal, and determining a first sound production position; determining a second sound production position by applying the voice signal and the physiological signal based on a sound production position determination model; and determining the sounding position of the sounding person based on the first sounding position and the second sounding position. According to the sound production position determination method and device and the vocal music practice system provided by the invention, sound source localization is performed on the voice signal, a small number of special sound production positions can be accurately detected, and meanwhile, the sound production position determination model can accurately detect the sound production position of a new sound production person based on voice, so that the sound production efficiency is improved. Therefore, the sounding position of the sounding person can be further accurately obtained by combining the first sounding position and the second sounding position.

The invention relates to the technical field of music teaching and learning vocal music breath practicing, in particular to a music teaching and learning vocal music breath practicing device which comprises a base and further comprises an air channel a, the air channel a is formed in the base, a connecting sleeve a is fixedly connected to an upper side plate of the base, three threaded sleeves a are fixedly connected to the interior of the upper side plate of the base and internally engaged with a lower side plate of a suspension pipe, and the upper side plate of the suspension pipe is fixedly connected with the air channel a. A suspension ball is slidably connected into the suspension pipe. Suspension pipes are meshed in the threaded sleeves b, the threaded sleeves b are transversely, evenly and fixedly connected to the lower side of the connecting plate, the air filtering cylinder is connected through the connecting sleeves a and the connecting sleeves b, the suspension pipes are connected through the threaded sleeves b and the threaded sleeves a, and by arranging a connecting column and a handle, the device can be conveniently held by hand, and the device can be conveniently placed; a learner can conveniently use fragmented time to improve the breath control ability, the device is assembled through a plurality of modules, the device is convenient to carry, and then the exercise time and place are not limited.

This invention discloses a breath training bottle for vocal music teaching with variable pipe diameter, belonging to the field of vocal training bottle technology. Its key technical features include a water-storage bottle body, with a support leg fixed to the lower side of one side of the water-storage bottle body. A bottle body tube is connected to the upper side of one side of the bottle body tube, with a cap attached to the upper end of the bottle body tube. A fixed tube seat is installed on one side of the upper end of the cap, and an air blowing tube is installed inside the fixed tube seat. A pipe diameter adjustment component is installed at the lower end of the air blowing tube. The pipe diameter adjustment component includes a pipe diameter adjustment end threaded onto the lower end of the air blowing tube, with connecting arms symmetrically fixed at the bottom end of the pipe diameter adjustment end. Through the cooperation of the threaded pipe diameter adjustment end and the frustum-shaped adjustment plug, the depth of the plug entering the air blowing tube can be flexibly adjusted, achieving continuous adjustment of the air outlet pipe diameter. This solves the core defect of poor adaptability in traditional fixed-diameter vocal training bottles, covering the needs of multiple scenarios such as vocal music teaching, amateur practice, and vocal cord rehabilitation.

The invention relates to the technical field of loudspeakers, in particular to a vocal music loudspeaker with light, which comprises a mounting panel, a loudspeaker opening is formed in the mounting panel, a loudspeaker body is mounted on the right side of the loudspeaker opening and comprises a frame, and a drum membrane, a first elastic metal ring and a second elastic metal ring are arranged on the left portion of the frame. The drum membrane fixing clamp is arranged between the first elastic metal ring and the second elastic metal ring, a baffle is fixedly arranged at the inner ring of the left end of the basin stand, heat dissipation holes are formed in the baffle, a metal substrate is arranged on the right side of the baffle, and the lamp strip is attached to the metal substrate; the right end of the metal substrate and the first elastic metal ring are arranged at an interval, and the interval is filled with sound absorption sponge. The outer edge of the tympanic membrane can drive the first elastic metal ring and the second elastic metal ring to follow up, the tympanic membrane is prevented from being damaged due to the fact that the tympanic membrane exceeds the vibration stroke, meanwhile, airflow exchange between the heat dissipation cavity and the outside is accelerated when the first elastic metal ring and the second elastic metal ring vibrate, and the heat dissipation effect of the heat dissipation cavity is improved.

The application discloses a natural emotional singing method and an emotional singing audio processing method, and belongs to the singing information field, and aims to solve the problems of fragmented training elements and single feedback system of a traditional vocal music teaching method. The technical scheme comprises six training modules combined by action guidance, emotion awakening and sound area training, and a training system for improving singing emotional expression capability based on a deep learning model for real-time extraction of user singing audio emotional indexes and generation of dynamic visual feedback.

A method and apparatus comprising computer code configured to cause a processor or processors to receive an audio signal obtained from a microphone, input the audio signal into frequency-domain Kalman filter (FDKF), input the audio signal and an output from the FDKF into a neural network, estimate, based on the audio signal and the output from the FDKF, and removing feedback signals from the audio signal by the neural network, recover, by a codec receiving an output from the neural network, vocal quality of a target vocal signal, and output a version of the audio signal in which the target vocal signal is enhanced by removal of the feedback signals from the audio signal by the neural network and by recovery of the vocal quality by the codec.

The application discloses an intelligent vocal music learning and assisting method and system based on artificial intelligence, and relates to the technical field of vocal music teaching.The method comprises the following steps: constructing a teacher pronunciation expression database comprising original pronunciation audio of multiple teachers, frame-level aligned real face videos and international phonetic transcription sequences, and generating teacher 3D face animation data for associated storage; acquiring learner audio data and extracting audio feature vectors; selecting the most similar target teacher based on audio feature similarity; inputting the learner audio into an audio-driven 3D face animation generation model to generate learner 3D face animation data; extracting the key frame sequences of the learner and the teacher for pronunciation actions; performing three-dimensional model difference calculation on the corresponding key frames to obtain frame-level difference quantization data, and generating visualized difference images.The application visualizes abstract vocal music pronunciation skills into intuitive 3D facial movements, realizes precise personalized guidance highly consistent with the individual characteristics of learners, and improves teaching efficiency.

The invention provides a vocal music training method based on deep learning. The vocal music training method comprises the steps of collecting vocal music training data through a multi-source sensor; preprocessing the vocal music training data, extracting acoustic features, expression features and physiological features, and constructing a multi-modal feature vector; the multi-modal feature vectors are input into a deep learning model, the deep learning model analyzes acoustic features through a convolutional neural network, analyzes physiological feature time sequence changes through a time recursive network, and fuses the multi-modal feature vectors through a cross-modal attention mechanism; based on the output of the deep learning model, real-time feedback information is generated, and the real-time feedback information comprises intonation correction suggestions, breathing rhythm guidance and emotion expression intensity scores; and dynamically adjusting the training difficulty according to the real-time feedback information, generating a personalized training plan, and updating parameters of the deep learning model. According to the embodiment of the invention, the problems of geographical limitation, low learning efficiency, difficulty in realizing personalized teaching and the like can be effectively solved.

The invention provides an automatic debugging method and system, electronic equipment and a storage medium. The method is used for a sound sensing device and comprises the steps that a test audio is played to a user, and the test audio is any one of words, syllables, music, voice, vocal music and pure tone; receiving response information of the user; determining whether the response information is matched with the test audio; when the response information is not matched with the test audio, storing the test audio as a reference optimized audio; determining a target distinctive speech feature corresponding to the reference optimized audio; determining a target operation parameter corresponding to the target distinctive speech feature according to a corresponding relationship between the distinctive speech feature and the operation parameter of the sound sensing device; and adjusting the target operation parameters to optimize the sound sensing equipment. The method is favorable for reducing the debugging cost and simplifying the debugging process.

1. Name of the product in this design: Vocal Practice Aid. 2. Purpose of this design: An aid for vocal practice. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

1. The name of the design product: vocal practice microphone. 2. The use of the design product: microphone for practicing vocal music. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention discloses an intonation device for displaying singing names. The intonation device comprises the following steps: A, selecting practicing tones, namely 12 tones; b, inputting a signal through an input unit; c, the single-chip microcomputer processing unit processes the input signal and quickly finds the code of the corresponding sound; and C, the single-chip microcomputer processing unit simulates and displays numbered musical notation singing name display of the standard tone according to the corresponding code. According to the method, the position of the numbered musical notation singing name can be simulated and displayed. The folk music enthusiasts only know the singing names of the numbered musical notation, so that the vocal music enthusiasts, the string music enthusiasts and the wind music enthusiasts can quickly link the made sounds with the pitch marks of the corresponding tones. The method is greatly helpful for a lover to quickly identify intonation deviation, and the intonation is remarkably improved.

The utility model relates to the technical field of vocal music teaching equipment, and discloses a voice recording device for vocal music teaching, which comprises a bottom plate, a voice recorder box is fixedly arranged on one side of the top end of the bottom plate and is connected with a sound pickup through a wire, and an adjusting box is fixedly arranged on the other side of the top end of the bottom plate and is connected with the sound pickup through a wire. Stand columns are slidably connected to the two sides of the top end of the adjusting box, a driving assembly for driving the stand columns to ascend and descend is arranged in the adjusting box, a cross beam is fixedly arranged at the top ends of the stand columns, and a cross rod is fixedly arranged in the middle of the cross beam; the stand column can support the cross beam, the driving assembly can control the stand column to stretch out and draw back automatically, the height of the sound pick-up is adjusted automatically through the cross beam in the stand column stretching-out and drawing-back process, operation is easy, good self-locking capacity is achieved, the stand column can be prevented from sliding off, stability is good, and safety and reliability are achieved. And supporting can be provided between the cross rod and the clamping assembly through the damping universal joint.

The invention discloses a sound visualization analysis method for vocal music teaching, and particularly relates to the field of music education, comprising sensor setting, data acquisition, sound data analysis, multi-dimensional correlation analysis and visualization. Through accurate sound and physiological data collection and in combination with multi-dimensional sound data analysis and correlation analysis, the vocal music skill and the sounding state of a singer can be comprehensively and deeply evaluated, the analysis result is intuitive and easy to understand through the real-time data visualization function, the singer and a teacher can quickly understand and make adjustment conveniently, and in addition, the analysis efficiency is improved. The method can also predict the change trend of sound indexes, provides a scientific basis for personalized teaching and training, and is beneficial to improving the vocal music teaching effect and the performance level of singers.

The utility model discloses a vocal music performance expression auxiliary correction mirror which comprises a base, and an adjusting assembly is arranged on the top of the base. The adjusting assembly comprises a first auxiliary block, one side of the rotating rod is fixedly connected with a second auxiliary block, the adjusting assembly further comprises an electric telescopic rod, one end of the electric telescopic rod is fixedly connected with a protruding block, and the top of the base is fixedly connected with a third auxiliary block. And one end of the convex block is rotationally connected with one end of the third auxiliary block. The utility model relates to the technical field of correction glasses. According to the vocal music performance expression auxiliary correction mirror, by starting an electric telescopic rod, a butt joint block can push a rotating rod to rotate, and finally the correction mirror body can be adjusted to adjust the angle, a triangular structure is formed among the rotating rod, the electric telescopic rod and a base, and all components at the three corners are rotationally connected; and when the length of the electric telescopic rod is changed, the number of angles in the triangle can be automatically and adaptively changed.

The invention relates to the cross technical field of computer technology and education informatization, in particular to a computer audio-visual method and system based on artificial intelligence and a computer readable medium, which are used for remote vocal music, dance or fitness action teaching. Image and audio data are converted into computable skeleton sequences and feature vectors through artificial intelligence, and are compared with standard data, so that the defects that traditional teaching depends on subjective experience of teachers, and real-time quantitative feedback cannot be realized are overcome. By constructing the unified virtual room and mapping all trainees into virtual characters therein, physical space isolation is broken, remote trainees can obtain the immediacy sense and team sense of'same-field training ', and learning motivation and interactivity are greatly improved. The evaluation result is instantly converted into visual elements (such as scores and special effects) in a virtual scene, visual and instant positive feedback or error correction prompts are provided for students, the skill acquisition process is accelerated, and a set of computer audio-visual method based on artificial intelligence is formed.

1. Name of the design product: Vocal music practice aid. 2. Use of the design product: This design product is used as an aid for vocal music practice. 3. Design key points of the design product: The overall shape of the product. 4. Picture or photograph that best shows the design key points: Perspective view.

To improve a game machine capable of outputting music pieces.SOLUTION: A game machine can execute multiple kinds of notice performances, can output an instrumental music piece during a period before development of a weak SP ready-to-win, can output a vocal music piece during a period after development of a strong SP ready-to-win, can execute a music piece limitation performance for limiting output of an instrumental music piece at the time of execution from among notice performances during a period before development of a weak SP ready-to-win, and can execute a music piece limitation performance for limiting output of a vocal music piece at the time of execution from among notice performances during a period after development of a strong SP ready-to-win.SELECTED DRAWING: Figure 14-68

To improve a game machine capable of outputting music pieces.SOLUTION: A game machine can execute multiple kinds of notice performances, can output an instrumental music piece during a period before development of a weak SP ready-to-win, can output a vocal music piece during a period after development of a strong SP ready-to-win, can execute a music piece limitation performance for limiting output of an instrumental music piece at the time of execution from among notice performances during a period before development of a weak SP ready-to-win, and can execute a music piece limitation performance for limiting output of a vocal music piece at the time of execution from among notice performances during a period after development of a strong SP ready-to-win.SELECTED DRAWING: Figure 14-68

The invention relates to the technical field of loudspeaker boxes, and provides a portable loudspeaker box for vocal music singing teaching, which comprises a shell, a connecting cover is mounted on the shell, a through hole is formed in the connecting cover, a fixing block is fixedly arranged at the bottom of the shell, a supporting assembly is mounted at the bottom of the fixing block, and the supporting assembly is connected with the connecting cover. A rubber connecting shaft is rotatably installed below the supporting assembly, a suction cup is fixedly arranged at the bottom of the rubber connecting shaft, an inner groove is formed in the rubber connecting shaft, a communicating groove is formed between the rubber connecting shaft and the suction cup, an exhaust hole is formed in the side face of the fixing block, and a second groove is formed in the middle of the fixing block. By means of the technical scheme, the problems that an existing loudspeaker box cannot quickly clean dust in the loudspeaker box through a supporting structure, the connecting cover cannot be cleaned through a sealing adjusting structure, the existing loudspeaker box is inconvenient to carry, and the sound amplification direction is inconvenient to adjust are solved.

This application provides a vocal practice assistance system based on vocal cord fatigue analysis, comprising: a surface-mounted electrode for attaching to a detection target to acquire electromyographic (EMG) signals; an EMG signal acquisition module for acquiring the EMG signals transmitted by the surface-mounted electrode and performing analog-to-digital conversion; a data transmission and reception module for sending the EMG signals acquired by the EMG signal acquisition module to a host computer and receiving relevant information; a preprocessing module for preprocessing the EMG signals transmitted by the data transmission and reception module to reduce noise; a signal separation module for separating the preprocessed EMG signals; a feature extraction module for acquiring the time-domain and frequency-domain features of the EMG signals; and a fatigue analysis module for linearly fitting the time-domain and frequency-domain feature curves and analyzing the vocal cord fatigue trend through the slope of the linear fitting equation. This system can monitor and analyze the degree of vocal cord fatigue in real time and provide a convenient and reliable vocal practice assistance device for vocal professionals.