38 results about "Vowel" patented technology

The invention relates to the technical field of audio signal processing. The invention provides a method, system and device for predicting pulmonary nodules through sound and a storage medium. The method comprises the following steps: in a quiet test environment, directionally collecting a sound signal of a patient through an audio sensor; wherein the sound signals comprise breath sounds, cough sounds, vowels and sentences; performing noise reduction processing on the collected sound signals to obtain a noise reduction data set; extracting multi-dimensional voiceprint features from the noise reduction data set, and constructing a sound feature matrix; and performing multi-modal fusion analysis on the sound feature matrix and clinical data of the patient, inputting the sound feature matrix and the clinical data into a sound prediction model optimized by a focus loss function, and outputting a pulmonary nodule risk prediction result and a visual diagnosis report. The problems that the misdiagnosis and missed diagnosis rate is high, the radiation risk is large and the equipment dependence is strong when the pulmonary nodules are examined by the existing iconography, and the characteristic analysis is single, the noise immunity is poor and the screening accuracy is insufficient in the sound detection technology are solved.

The present invention relates to a system and method configured for analysing acoustic parameters of speech to detect, diagnose, predict and / or monitor progression of a condition, disorder, or disease, and more particularly, any of paediatric and adult neurological and central nervous system conditions including but not limited to low back pain, multiple sclerosis, stroke, seizures, Alzheimer's disease, Parkinson's disease, dementia, motor neuron disease, muscular atrophy, acquired brain injury, cancers involving neurological deficits, paediatric developmental conditions and rare genetic disorders such as spinal muscular atrophy. The system and method extracts a first formant data set from words spoken by an individual and uses these to classify the vowels in the words on a first computing device, such as a mobile smart phone equipped with a microphone into which an individual speaks. The system stores at least some of these frequencies for the vowel formants in a second formant data set as a recorded file and provides the second formant data set as input to acoustic metrics to generate score data from which an assessment is made to determine the articulation level of the vowels in the words spoken by the individual, allowing allow for detection, diagnosis, prediction and / or monitoring progression of the condition, disorder, or disease.

The invention discloses a multidirectional sliding Chinese character pinyin input method and a matrix type keyboard layout system, and belongs to the technical field of human-computer interaction of touch screen equipment (IPC classification number: G06F3 / 0488, G06F3 / 0323G06F 40 / 274). Aiming at the problems of complex vowel operation redundancy, initial and final combination conflict and the like in the existing sliding input method, the invention provides the following schemes: 1, the multidirectional sliding input method comprises the following steps of: starting sliding from any initial consonant or vowel (containing a zero initial consonant 0 / er key) on the basis of a matrix keyboard layout; different vowels or vowel combinations are mapped every time sliding is performed by one key in different directions or continuous sliding is performed. 2, multi-direction sliding input logic: defining an 8-direction sliding mapping er to be rightward-or-generated from e in a layout E; the method has the technical effects that the input efficiency is improved by more than 60% (high-frequency syllable steps are reduced by 70%), the false touch rate is lower than 5%, the national standard pinyin library is covered by 100%, and the method is obviously superior to a traditional touch screen input scheme.

A method of providing an instructional scaffold to person learning to read English language comprises displaying printed matter to the learner in the form of lists. Preferably text stories. The normal spacing of the letters in words is kept intact; in a first part of the method the rime portions of monosyllable words are bolded and made larger than the onset portions; and in a second part of the method, which also may be used independently, the sequential syllables of multisyllable words are emphasized by alternating plain font with bolded font and the long vowels are identified, for example by underscore, again with the words of any text being kept intact.

A data structure and associated methods for analysis of a continuous 1,197,000-letter unvocalized Hebrew string referred to as the Word of God (WOG). The data structure contains only the twenty-two classical Hebrew letters and their five final forms, with no spacing, punctuation, vowelization, or editorial symbols. Intrinsic placement of the final letters enables deterministic segmentation of the string into 305,490 lexical units and 23,206 verses without external conventions. Fixed letter-number assignments provide a numeric architecture for evaluating substrings, detecting alterations, identifying encoded mathematical correspondences, and performing pattern analysis. The system preserves full semantic range by supporting multiple morphologically valid interpretations of unvocalized Hebrew strings. Methods for segmentation, numeric evaluation, reconstruction, integrity verification, semantic analysis, and mathematical pattern detection are provided thereby providing a reproducible foundation for computational and linguistic research.

: A method for enabling comprehension of speech by tactile stimulation is provided. The method includes steps as follows: receiving an audio input; performing an analog-to-digital conversion on the audio input; performing a DFT to convert the audio input to a frequency domain; extracting key features of the audio input based on a band of the audio input, wherein the key features contain frequencies that are representative of at least one vowel; and converting frequencies of the extracted key features to a range of tactile frequencies, which comprises performing a mapping process on the frequencies to shift or map them into a subset, such that the mapping process transfers the frequencies from a high-frequency interval to a low-frequency interval, wherein the low-frequency interval is a perceivable range of tactile frequencies.

The application discloses an input method, device and system based on number sequence and number sequence vowel definition and symbol mapping, which comprises the following steps: defining a number sequence and a number sequence vowel set, wherein the number sequence is a fixed sequence of numbers 1-9, 0 and an extended character, the number sequence vowel set comprises 11 groups of vowels arranged according to the number sequence, and each group of vowels corresponds to a unique number sequence coding bit; establishing a mapping relationship between the 11 groups of vowels and a number sequence input unit, wherein the number sequence input unit comprises at least 10 digital key positions and an extended character key position arranged according to the number sequence; and generating a candidate word list according to the defined number sequence and number sequence vowel set and the mapping relationship in response to a user input operation. The application solves the problem of inconsistent coding logic and multiple keystrokes of vowels in the prior art, significantly improves the input efficiency of Chinese pinyin, supports multiple input modes to share a unified coding system and reduces the learning cost of users.

To provide English teaching materials helping students intuitively acquire English pronunciation.SOLUTION: There is provided an English teaching material comprising a position identification member and a plurality of vowel cards. The position identification member includes a bimaxillary display for roughly representing a lateral cross-section of both jaws of a person, and a plurality of identifiers for respectively identifying a plurality of positions of a tip of the tongue during pronunciation. The plurality of vowel cards are each assigned to a different English vowel. The plurality of vowel cards have, on each one side, a face symbol imitating a human face and one or two of a plurality of identification displays. The face display includes a mouth shape diagram for graphically representing the mouth shape when pronouncing the corresponding vowel. The plurality of identification displays respectively have the same form as any of the plurality of identifiers.SELECTED DRAWING: Figure 1

This product is a notebook paper with five lines representing vowels next to the writing space, with the vowels A, I, U, E, O marked at the beginning of each line, visualizing the finger movements for vowels when reading by hand. It can be used vertically or horizontally depending on the purpose. After writing the letters, mark the vowel positions on the five lines, connect the marks with lines, and visualize the vowels.

Provided are a method, apparatus, and medium for recognizing tones of speech. The method comprises: detecting the duration position of a vowel of a vowel in a speech to be recognized; detecting a tone core portion of the speech to be recognized based on the duration position of the vowel of the vowel; and identifying the tone category of the speech to be recognized based on the tone core portion. Thus, according to at least one embodiment of the present disclosure, the tone core portion can be more accurately detected within the duration position of the vowel of the vowel, thereby more accurately identifying the tone category.

The invention provides an information input device and a pinyin input method thereof. In a pinyin input mode, selective input of information is realized through an operation signal of a physical key, and the information input device comprises an initial input unit which is configured to switch initial pages in response to an operation signal of a first key and determine initial in the initial pages in response to an operation signal of a first rocker; the vowel input unit is configured to switch vowel pages in response to the operation signal of the second key and determine vowels in the vowel pages in response to the operation signal of the second rocker; and the Chinese character input unit is configured to respond to a pinyin confirmation signal of the third key, generate candidate Chinese characters according to the determined initial consonants and finals, and input selected Chinese characters according to operation signals of the cross key and the fourth key. The invention provides a technical scheme which accords with the operation characteristics of a general handle and can remarkably improve the pinyin input efficiency.

A computer-implemented method can include determining a speech transition within a speech signal, the speech transition including a change of sound; determining a mouth state based on the speech transition; determining a vowel transition during a vowel sound within the speech signal; and modifying a facial feature of an avatar based on the mouth state and the vowel transition.

The invention provides a vowel recovery method and device, electronic equipment and a storage medium, and belongs to the technical field of natural language processing, the vowel recovery method comprises the steps that a first to-be-processed text is acquired, and the first to-be-processed text comprises a first text needing vowel recovery; the first to-be-processed text is input into the vowel recovery model for variable note label synchronous prediction, prediction labels output by the vowel recovery model are obtained, and the prediction labels are three types of variable note labels corresponding to each character in the first text; and determining a target text after vowel recovery based on the first to-be-processed text and a prediction label output by the vowel recovery model. In the process, the three types of variable note tags corresponding to each character in the first text can be synchronously predicted, and conflicts among different variable note tags are avoided, so that the variable note tag is accurately predicted for each character in the first to-be-processed text, and the accuracy of vowel recovery is improved.

The present application proposes a vocal singing practice quality grade evaluation method of fractional order spectrogram deep learning, including the following steps; Step S1, collect the audio signal of the singer's vocal vowel singing practice, and according to the singing index, label the corresponding quality grade, construct the sample data set, and use it for model training, testing and verification; Step S2, convert the audio signal into a series of fractional order spectrograms; Step S3, construct the fractional order spectrogram deep feature extraction network based on DenseNet and channel attention mechanism in the model, input the extracted fractional order spectrogram deep features into the BiLSTM network, and extract the time sequence features of the singing practice signal; Step S4, the quantum fireworks algorithm is used to optimize the hyperparameters of the kernel extreme learning machine of the model, and the extracted time sequence features are mapped to a high-dimensional space for quality grade decision, forming the evaluation result; Step S5, train the model; The present application can better adapt to the characteristics of non-stationary signals and provide more accurate spectrum analysis.

The edge device-oriented lightweight voice band expansion method, device, terminal and medium provided by the application belong to the technical field of voice signal processing, and the method comprises the following steps: obtaining a logarithmic domain narrowband audio signal amplitude spectrum and a logarithmic domain mixed amplitude spectrum; constructing a white noise amplitude spectrum; inputting the logarithmic domain narrowband audio signal amplitude spectrum, the logarithmic domain mixed amplitude spectrum and the white noise amplitude spectrum into a trained voice bandwidth expansion model to generate a first high-frequency component corresponding to a consonant in the narrowband audio signal and a second high-frequency component corresponding to a vowel in the narrowband audio signal, and then obtaining a predicted amplitude spectrum; expanding phase information of the narrowband audio signal, generating a wideband audio signal according to the predicted amplitude spectrum and the expanded phase information of the narrowband audio signal, and outputting the wideband audio signal. The voice bandwidth expansion model is used to reconstruct the consonant, so that the reconstructed consonant component has higher fidelity, and the intelligibility of the reconstructed voice is ensured.

The application provides a vowel restoration method and device, electronic equipment and storage medium, and belongs to the technical field of natural language processing, and comprises the following steps: obtaining a first to-be-processed text, the first to-be-processed text comprising a first text requiring vowel restoration; inputting the first to-be-processed text into a vowel restoration model for multi-vowel symbol label synchronous prediction to obtain a predicted label output by the vowel restoration model, the predicted label being three types of vowel symbol labels corresponding to each character in the first text; and determining a target text after vowel restoration based on the first to-be-processed text and the predicted label output by the vowel restoration model. In this process, three types of vowel symbol labels corresponding to each character in the first text can be synchronously predicted, avoiding conflicts between different vowel symbol labels, so that the vowel symbol label of each character in the first to-be-processed text can be accurately predicted, thereby improving the accuracy of vowel restoration.

The Chinese phonetic alphabet tone corner code labeling method is used for supplementing and expanding a currently executed Chinese phonetic alphabet scheme in actual use and is used for reading correct Chinese phonetic alphabets. An existing Chinese pinyin scheme is composed of letters and tones, and a standard mode that pronunciation of Chinese characters is displayed in an integral up-and-down structure mode is adopted. However, on the basis of an information digital technology, information is expressed in a one-way structure mode from left to right, and pronunciation of Chinese characters is often directly expressed by phonetic alphabets without upper tones. According to the scheme, a single form of an up-and-down structure of which tones are marked on finals in a Chinese pinyin scheme is expanded in a left-and-right structure form, and the scheme is more suitable for a left-to-right structure expression mode of a modern information digital technology. The method can complement the missing tones of the existing Chinese pinyin scheme in use, provides correct Chinese character pronunciation, and does not affect listening, speaking, reading and writing of Chinese characters. Strengthening Chinese phonetic alphabets is an important role as a tool for assisting Chinese character pronunciation.

This disclosure provides a method, apparatus, device, and storage medium for segmenting Chinese speech signals. The method includes: sampling a target audio signal containing speech corresponding to a target Chinese text to obtain signal amplitudes corresponding to multiple sampling points; performing speech endpoint detection on the target audio data based on the signal amplitudes corresponding to the multiple sampling points to obtain multiple speech segments in the target audio data; determining the vowel position sequence corresponding to the target speech segment based on the formant energy of the speech signal in the target speech segment; determining syllable segmentation points and initial / final segmentation points of the target speech segment based on the signal amplitudes of sampling points between two adjacent vowel positions in the vowel position sequence and the initials and finals of the corresponding Chinese text segment; and segmenting the target speech segment based on the syllable segmentation points and initial / final segmentation points to obtain segmented speech primitives. This disclosure improves the accuracy of speech signal segmentation.

A hearing system (2) having a hearing instrument (4) worn in or at a user's ear and a method for operating the hearing instrument (4) are provided. During operation of the hearing instrument (4), an ambient sound signal from the hearing instrument (4) is captured and processed to support the user's hearing. The processed sound signal (O) is output to the user. In a start point identification step at the beginning of the signal processing, the captured sound signal (I) is analyzed to identify a start point of a speech vowel. In a start point enhancement step, the processed sound signal is instantaneously modified when the start point of the speech vowel is identified to enhance the start point. In this context, the processed sound signal (O) is instantaneously modified by selectively increasing the signal level of the processed sound signal in a first frequency sub-range.

The application belongs to the technical field of lip language mouth shape analysis, and discloses a GNN-LSTM Chinese lip language classification method based on node multi-association graph information fusion. Lip key points are represented by three structures of adjacency graph, symmetric graph and upper and lower lip relationship graph. High-dimensional space-time features are extracted under the synergistic effect of graph convolutional neural network and long short-term memory network, the space-time global correlation between lip key points is effectively captured, and the mouth shape class is divided based on initial and final vowels. The multi-level collaborative relationship between initial and final vowels is considered, the influence of mouth shape similarity and visual ambiguity on model performance is reduced, a mouth shape library is established by using the extracted high-dimensional space-time features, the lip shape and corresponding pinyin are more discriminatively mapped and induced, the influence of mouth shape similarity and visual ambiguity on model performance is reduced, the method can adapt to complex changes and many-to-one mapping phenomena in actual pronunciation processes, and effectively enhances the accuracy and robustness of subsequent mouth shape classification.

This invention discloses a method for recognizing vocal styles based on time-frequency refined analysis. The process is as follows: First, a fundamental frequency estimation and harmonic labeling step is performed. The short-duration vowel portion of the vocal signal is first used for fundamental frequency estimation. This estimation employs a frequency estimation algorithm combining time-domain autocorrelation and narrowband spectral energy. Then, based on the estimated fundamental frequency, adaptive harmonic labeling is performed on the spectrum to accurately identify all harmonics. Next, a time-frequency refined analysis step is performed. The vocal signal is refined and features are extracted from both the time and frequency domains, with a focus on periodic variations and harmonic structures. Finally, a support vector machine (SVM) model training and recognition step is performed. The extracted features and corresponding vocal style labels are used to train the SVM model. After training, the model can be used for vocal style recognition. The style is obtained by using the feature vectors extracted from the vocal signal as input.

The invention discloses a multi-dimensional speech adaptive training method and system. The method comprises the following steps: collecting historical training data and training time intervals of a user, and judging whether vowel training is started or not; acquiring real-time training data of a user, and sequentially performing loudness judgment, pitch exercise judgment and vowel space area standard judgment; and respectively calculating corresponding vowel space area target adjustment coefficients according to the age and gender classification of the user, and entering different training formulating modes based on the size comparison of the second target and the first target to generate a personalized vowel exercise plan. Through dynamic acquisition and quantitative analysis of multi-dimensional voice parameters, self-adaptive adjustment of training content and difficulty is realized, manual fine adjustment is supported, the problems of parameter solidification, insufficient personalization and weak feedback mechanism in an existing voice training system are effectively solved, and the pertinence, adaptability and rehabilitation effect of training are improved.

The invention discloses a classical poem recitation assisting method fusing initial and final analysis, and relates to the technical field of digital education, and the method comprises the steps: achieving the intelligent judgment and prompt of recitation rhythm and escort state based on the structural collection and analysis of recitation audio signals; the method comprises the following steps: acquiring and dividing a recitation audio into word segments through a voice recognition technology, and generating corresponding audio feature data information and text feature data information in combination with a poem structure; then judging whether the recitation duration is consistent with the poem structure or not through sentence level comparison, and providing a duration adjustment suggestion when the recitation duration is abnormal; on the basis that the recitation rhythm is normal, the vowel acoustic vector of each character is further extracted, and multi-level escort auxiliary suggestions are generated through initial and final difference analysis of the last character of adjacent sentences; according to the invention, through a process closed loop combining automatic acquisition, intelligent analysis and real-time feedback, the escort sensitivity and rhythm control ability of a learner are significantly improved.

The application provides a swallowing disorder patient detection method and system based on tensor decomposition, wherein the method comprises the following steps: obtaining speech data of swallowing disorder patients and normal persons, pre-processing the speech data, cutting off irrelevant information in the speech data and performing amplitude normalization operation; obtaining a spectrogram of the speech data, and constructing mixed tensors of different forms of vowels; sending the mixed tensors of different forms of vowels into a Tucker decomposition model with added orthogonal constraints, setting a proper rank to obtain a corresponding core tensor; unfolding the core tensor into a vector as a feature input, constructing a training feature set after feature selection, and training a swallowing disorder detection model; detecting to-be-detected speech data based on the detection model to obtain classification results of the swallowing disorder patients and the normal persons. The application is implemented based on speech, is simple to operate, has low cost, has no technical threshold during use, can safely and effectively detect swallowing disorder patients, and is convenient for follow-up.

The application relates to an improved pathological voice generation model and a construction method thereof, which comprises the following steps: S1, using all available pathological / a / vowel speech records under normal pitch in a sound data set as a training data set; S2, a training process is divided into training of a generator and training of a discriminator, both of which are alternately performed, the generator comprises a latent mapping network module and a transposed convolution and multi-receptive field fusion module; the discriminator comprises four discriminators with different cycle settings, which are used for evaluating and training intermediate waveform outputs after each upsampling of the generator; and S3, inputting a random noise vector into the trained generator, converting the random noise vector into new audio data by the generator, performing standardization processing on the generated audio data, and repeating the above steps to generate multiple new data.

A method, apparatus, and computing device for audio processing of lung function indicators are provided. The method can include obtaining at least one item of identity information related to a first user, obtaining at least one audio segment related to the first user, the at least one audio segment including at least one of a first audio segment containing a cough sound emitted by the first user, a second audio segment containing a blowing sound emitted by the first user, or a third audio segment containing a vowel sound emitted by the first user, processing the at least one audio segment to obtain a processed audio segment, determining, based on the at least one item of identity information, at least one predicted value of at least one lung function indicator of the first user, and determining, based on the at least one predicted value and the processed audio segment, a final predicted value of the at least one lung function indicator of the first user via a machine learning model.

An engine sound generating system, positioned in a moving object, includes a repeating section selection unit for recognizing at least one vowel section from an input sound source, and selecting a repeating section to be repeated based on the vowel section; a repetitive waveform generating unit for generating a repetitive waveform based on the selected repeating section; and an engine sound output unit for generating and outputting an engine sound by interpolating the generated repetitive waveform.

The embodiment of the invention discloses a Chinese speech signal segmentation method and device, equipment and a storage medium, and the method comprises the steps: carrying out the sampling of a target audio signal containing the speech corresponding to a target Chinese text, and obtaining signal amplitudes corresponding to a plurality of sampling points; performing voice endpoint detection on the target audio data based on the signal amplitudes corresponding to the plurality of sampling points to obtain a plurality of voice segments in the target audio data; determining a vowel position sequence corresponding to the target voice segment based on the formant energy of the voice signal in the target voice segment; determining syllable segmentation points and initial and final segmentation points of the target speech segment based on signal amplitudes of sampling points between two adjacent vowel positions in the vowel position sequence and initial and final consonants of the Chinese text segment corresponding to the target speech segment; and based on the syllable segmentation points and the initial and final segmentation points of the target voice segment, segmenting the target voice segment to obtain segmented voice elements. According to the embodiment of the invention, the accuracy of voice signal segmentation can be improved.

Embodiments include systems and methods for detecting physiological parameters or health metrics using segmented audio signals. A system prompts a user to produce structured vowel sounds, minimizing audio conditioning or modulation artifacts, such as automatic gain control. The system analyzes voiced-sound segments using time-domain and / or frequency-domain techniques to extract a fundamental frequency and identify periodic modulations corresponding to cardiac pulses. Signal integrity criteria are applied to ensure robust data quality. Physiological parameters, such as heart rate, heart rate variability, and additional metrics, are generated based on the detected modulations. Real-time alerting and feedback mechanisms enable reacquisition of audio samples when signal quality is insufficient and fails quality or signal criteria thresholds or fails expected metrics thresholds.