Speech Analysis TRIZ Cases

ToneFilling patches spectral patterns into the MDCT spectrum to synthesize sinusoids, reducing warbling artifacts in low bit rate audio codecs.

A CELP encoder adjusts spectrum peak amplitude to enhance decoded music quality.

A coding apparatus normalizes low band spectra via sub-band amplitude search to flatten signal components before extension.

An automated text adaptation system translates and highlights cognates to support language learners.

A dual microphone voice activity detector estimates signal and noise levels at each sensor to distinguish target speech from distant disturbances.

A noise suppression device detects shock noise through input signal intensity changes to generate high-quality emphasized sound.

A motion analyzer uses dual microphones and acceleration sensors to detect subject speaking and body movement.

An automated localization mechanism extracts text content from files and merges translations back while preserving structure.

Cascaded subpixel convolutional neural networks extend narrowband speech signals to wideband audio by interpolating missing spectral samples.

A playback speed control apparatus varies audio tempo by determining optimal input and output frame lengths for efficient overlapping operations.

A watermark detector inspects multichannel audio subchannels to verify proper distribution of embedded signals across channels.

Dynamic band selection in scalable audio encoding uses lower-layer decoded signals to target residual energy, fixing fixed-position quantization limits.

Encoder updates adaptive spectral code book with synthesized frequency representations to reduce buzzing distortion in noise-like sounds at low bit rates.

A sound reproducing apparatus adapts a fixed head-related transfer function using listener data to generate target audio signals.

A conditioning apparatus synthesizes audio filler signals to fill spectral valleys between local amplitude maxima in frequency spectra.

Predictive quantization estimates second channel linear prediction coefficients from the first channel, reducing quantization errors at low bit-rates.

A speech signal processing method weights predicted high frequency band components against previous frame data to synthesize wideband audio output.

A call recording system uses offline machine learning to detect active calls and store audio locally without external software.

Acoustic pressure analysis detects earphone wearing status using feedforward and feedback sound measurements.

An audio conversion device transmits compressed audio in its original format to preserve multi-channel sound quality.

U-Net CNN architecture processes audio signals using multi-scale parallel convolution paths to capture scale-relevant features and harmonics.

A speech quality assessment algorithm samples reference and degraded signals into paired frames to calculate a difference function representing signal disturbance.

System analyzes audio signals to assess acoustic performance, providing user tasks to adjust settings without external technician assistance.

Time advanced excitation generation improves speech representation accuracy in source coding systems.

A system generates customized response messages by analyzing recipient availability and relationship history.

A voice separation system uses ultrasonic signals for precise time synchronization and calculates clustering ranges to align microphone data.

Estimating and subtracting late reverberation via adaptive filtering reduces word error rates in speech recognition by canceling reflected voice components.

Stereophonic energy detection system converts radio frequency signals into audible tones for spatial awareness.

A sound source direction estimation device calculates phase differences from a microphone array to identify speaker location.

Segmenting spectrograms around energy extreme points extracts local features that reduce noise sensitivity and improve matching accuracy.

Segmenting audio into high and low fidelity streams replaces lost data, resolving network loss without excessive bandwidth overhead.

An audio decoder adjusts the Nyquist frequency based on spectral content to transform signals between domains.

Audio analysis agents determine network latency and display visual indicators to prevent speech confliction during high latency sessions.

Replacing fixed codebooks with neural networks reduces bit-rate and memory while maintaining speech quality.

Binary masks segment speech from noise in hearing aids, improving intelligibility while reducing processing complexity.

Encoding device identifies silent audio channels to reduce unnecessary data transmission and improve multichannel signal efficiency.

Acoustic analysis system estimates exhaled lung volume from speech signals, replacing hospital spirometers with remote home monitoring.

A wireless transmission device selects encoding modes based on receiving device function modules to ensure signal compatibility.

A spectral band replication encoder synchronizes frame boundaries with grid lines to reduce decoding delay.

A watermarking technique embeds data in low priority codebook tracks to preserve speech quality.

A neural network audio encoder applies a perceptually weighted error function to optimize signal processing.

A household intelligent robot identifies users through voiceprint and facial image matching to retrieve personal profiles.

Audio signal processing circuit modifies intermediate signals to suppress wind noise interference and preserve directivity.

Specialized neural networks generate reliability outputs alongside decisions, reducing misidentifications in speaker authentication tasks.

A multi-channel decoder uses a cancellation channel calculator to subtract center channel components from transmission signals.

A neural network generates a joint probability distribution from previous sample data to guide a sample generator.

A generative neural network synthesizes synthetic faces from input videos to replace original identities while preserving behavioral data.

A sonification system converts continuous integration build data into auditory signals using musical techniques like arpeggio and legato.

Encoding apparatus embeds second frequency band components into first band signals, enabling efficient compression of wide-band audio without quality loss.