Speech Analysis TRIZ Cases

A method adapts inter-channel time difference search complexity based on audio channel quality to determine precise timing parameters.

A sound recognition device fuses emotion data with voice segments to identify speakers.

A device calculates an encoding matrix from directive microphone look directions to produce First Order Ambisonic signals.

Extracts frequency-domain data directly from encoded audio bitstreams to generate identification fingerprints without full decoding.

Stochastic gain modeling tracks non-stationary noise energy, resolving estimation delays in hearing aids.

Sealed earphone cavities boost microphone signals while adaptive filtering removes movement interference to ensure precise heart rate detection.

Scaling lost frame high-band signals with low-band gain variations ensures consistent interframe energy trends, reducing noise in voice transmissions.

A neural network merges beamforming and channel shortening to process multi-channel audio inputs.

A pre-learned model estimates reverberation kernels to enhance sound data without prior speaker knowledge.

A response quality evaluation device calculates index values from sales dialogue data and displays them on a terminal.

An inverse quantization method uses bit shifting to calculate interpolated values for audio decoding.

A phonetic key generation system creates full, replaced-vowel, and no-vowel keys from Japanese Kana characters to enable database record retrieval.

The system builds voice models from natural conversation data to resolve false rejections caused by ambient noise and voice changes over time.

Dividing audio signals at tonal system boundaries reduces audible overlaps and artifacts while suppressing acoustic feedback.

Dual microphone wearable device applies active noise cancellation and frequency spectrum matching to suppress background noise interference.

A speech encoder adds a predetermined noise signal derived from inverse pitch correlation to generate a simulated signal for linear predictive coding analysis.

A noise cancellation system matches latent space vectors to retrieve configuration parameters.

An object control system deduces user feelings to manage internal states and determine appropriate actions.

Joint filtering of mid and side signals reduces computational complexity while maintaining spectral distribution and preventing in-head localization.

Segmented codebook search restricts the search space to improve speech quality at lower bit rates.

A speech enhancement device adjusts signal gain based on elapsed time from the start of a speech production section.

Fast Fourier transform extracts spectral slope differences from voice signals to identify alcohol consumption remotely.

A noise filling technique applies a spectrally global tilt to adjust energy distribution across frequencies in audio codecs.

Dynamic smoothing filters adjust to spectral features, resolving accuracy and robustness trade-offs in non-coincident microphone scenarios.

Combines intermediate spatial and stationary noise gains to suppress background audio signals.

Local clock substitution and zero padding mitigate discontinuities during source switching to prevent popping sounds.

Encoding separate object and reverberation signals resolves the contradiction between low bit rate and accurate sound scene reconstruction.

A normalization matrix trains on identity vectors to maximize intra-class similarity for voice segments.

Audio processing module computes resampling ratios to select time or frequency domain conversion paths, reducing computational complexity and memory overhead.

Flexible layered coding optimizes bitstream routing and irregular quantizers to resolve quality loss in heterogeneous networks.

A neural network processes complex spectrograms to separate multi-speaker audio signals using iterative phase reconstruction layers.

A virtual duplex audio system segments speech bandwidth into sub-bands to enable echo cancellation during double-talk conditions.

Low-complexity neural networks paired with phase estimation algorithms determine target phases, resolving processing efficiency bottlenecks in mobile devices.

A noise filling apparatus omits redundant data transmission to reduce bitstream volume.

A neurological training system navigates a graph data structure using user gesture inputs to present dynamic audible outputs.

Segmenting audio data by frequency band prioritizes lower bands to ensure reliable transmission and reduce resource usage.

Monitoring audio transducer admittance enables silent biometric authentication without audible test signals.

A decoding apparatus selects audio encoded bit streams and skips overlap-and-add processing during rapid switching operations.

A dual-channel noise processing system uses a selector to route distinct noise estimates for different frequency bands to an attenuator.

A signal analysis controller detects non-stationary events in engine order cancellation systems to prevent filter mis-adaptation.

An apparatus applies frequency domain oversampling selectively to transient audio signal portions using a spectral converter and time converter.

A speech decoder calculates high frequency time envelopes using multiple low frequency band envelopes to adjust signal waveforms.

High band audio signal scaling prevents energy calculation saturation in fixed-point gain parameter estimation.

Continuous noise estimation using spectral smoothing resolves the contradiction between outdated estimates and non-stationary babble noise tracking.

Dynamic signal type detection routes spatial and downmix audio through specialized processing paths to minimize artefacts and preserve fidelity.

A unified audio bitstream multiplexes Dolby Digital Plus and AAC data within auxiliary fields to enable cross-platform decoding.

A parameter generated from voiced signal sequences using pitch estimation and frequency transforms.