247 results about "Vocal music" patented technology

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 14-77

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 music recommendation, and discloses a multi-source data intelligent music recommendation method and system, a storage medium and equipment, and the method comprises the steps: collecting multi-source music data, and carrying out the fusion processing of the collected multi-source music data; the method comprises the following steps: identifying and extracting music related entities in data and relationships among the entities, constructing a music ontology and reasoning music knowledge to construct a music knowledge graph; a user portrait is comprehensively constructed by extracting explicit features of a user, constructing a user implicit behavior model, mining a time sequence mode and integrating cross-platform data; user emotion and situation changes are captured in time through context sensing, and a recommendation strategy is adjusted in real time; and carrying out personalized recommendation by combining collaborative filtering, extracted vocal music features and semantic features and a music knowledge graph. Through the method, a multi-source data intelligent music recommendation system is realized, and a highly personalized and context-aware music recommendation service is provided for the user.

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.

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 14-82

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 14-77

The invention provides a personalized vocal music intelligent teaching system and a computer program product. The system comprises a front-end data acquisition device and a background server. The front-end equipment is provided with a physiological, psychological and physique parameter determination module; the background server is provided with a vectorization processing device which comprises vectorization, fusion, matching and output units. The physiological module determines physiological parameters, the psychological module determines psychological parameters, and the physique module determines physique parameters. The vectorization module converts parameters into vectors, the fusion unit obtains user feature vectors, the matching unit matches tracks in a vocal music library, and the output unit displays the matched tracks. According to the method, the physiological parameters of the target user are combined with the psychological characteristics and the physical conditions to comprehensively understand the sound expression potential and limitation of the user, the accuracy and depth of sound characteristic positioning are ensured, the physiological, psychological and physical parameters are fused into the user characteristic description vector, and the comprehensive index provides a scientific basis for accurate music selection.

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.

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 14-90

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.

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

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.

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 14-97

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

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 utility model discloses a preschool education vocal music rhythm training device, and relates to the vocal music training field, the preschool education vocal music rhythm training device comprises a base plate, a screen, a telescopic column, a pedal and an L-shaped panel, one side of the upper surface of the base plate is fixedly provided with a stand column, the upper end of the stand column is fixedly provided with a storage box, one side of the storage box is opened, and the column wall of the stand column is fixedly provided with a fixing rod; the L-shaped panel is fixedly arranged at the tail end of the fixing rod, two L-shaped pressing rods are symmetrically arranged on the front face of the L-shaped panel, the bent ends of the two L-shaped pressing rods are slidably inserted into and extend to the back face of the L-shaped panel, the same connecting plate is fixedly arranged at the bent ends of the two L-shaped pressing rods, and a first spring is fixedly arranged between the side face of the connecting plate and the back face of the L-shaped panel. Various types of training books can be placed, a trainee can find, take and use the books conveniently, meanwhile, the opened training books can be pressed, automatic jumping of pages of the opened books for vocal music training is avoided, and the preschool education vocal music rhythm training effect is improved.

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 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.

The invention relates to the technical field of teaching display, and discloses a display support for vocal music piano teaching, which comprises a base, moving wheels are fixedly assembled at the bottom of the base, a support frame is fixedly mounted at the top of the base, a second sliding groove is formed in the outer wall of the support frame, and a piano placement display assembly is arranged on the inner wall of the second sliding groove. A lifting rod is slidably connected to the top of the supporting frame, and a third sliding groove is formed in the outer wall of the lifting rod. A controller transmits a signal, so that a motor can start to work, then a rotating shaft can drive a straight groove handle to rotate, after the straight groove handle rotates to 90 degrees, a music score placing frame can be pulled downwards from the outer wall of the straight groove handle by pulling a handle, and a music score for vocal music piano teaching can be placed on the inner wall of a limiting fixing belt to be fixed; therefore, the device can achieve the purpose of better teaching display, can improve the teaching efficiency, and provides convenience for teachers and students at the same time.