Speech Analysis TRIZ Cases

Automated voice print comparison detects imposture in spoken tests, replacing manual verification to reduce processing time and improve reliability.

Dynamic signal modeling and parameter changes reduce keyboard click noise without canceling voice or introducing audible artifacts.

A trained model extracts voice characteristics using convolutional and residual layers to optimize acoustic representations.

A non-Gaussianity index analyzes digitized snore audio signals to estimate sleep disorder parameters using electronic processors.

An apparatus inserts a bit width field into audio frames to resolve parameter mismatch contradictions between sending and receiving ends.

A multichannel acoustical signal processing apparatus extracts common feature data from individual channels to execute synchronized time compression and expansion.

A signal processing apparatus determines filter coefficients using eigenvalues to transform input audio signals into output audio signals.

An arithmetic decoder modifies numeric context representations using subregion values to process spectral data efficiently.

Dynamic speech model updates separate voice from background noise during audio communication sessions.

A signal classifying method buffers spectrum fluctuation parameters to calculate frame ratios for accurate speech and music detection.

A mobile audio processing system expands channel signals to improve playback effects.

Integrated SoC codec processes USB and FM audio signals using a shared clock system to minimize timing jitter.

Voice activity detection filters conference noise using energy and zero crossing rate analysis, eliminating manual user intervention.

Multi-microphone audio systems identify crosstalk by comparing segment time differences against reference values to isolate interference signals.

Embedder inserts descriptive metadata into content, reducing detection difficulty and interference when extracting multiple watermarks.

A binaural room impulse response filter generates spatial audio by combining head-related impulse responses with directional acoustic reflections.

Segments Ambisonics channels by spatial resolution to reduce encoded footprint while maintaining high-fidelity reproduction.

Embedding watermarks into frequency coefficients during transformation enhances resilience against unauthorized tampering and removal.

Warped domain transformation and segmented gain-shape coding reduce computational complexity while maintaining quantization quality.

A voice quality evaluation method segments data packets into silence and voice frames to extract frame loss events for precise assessment.

Segmenting binaural room impulse response filters lowers computational complexity while maintaining sound fidelity for surround sound experiences.

A spatialization data prediction system selects from multiple models to reconstruct multi-channel audio signals.

A distortion limiter adjusts upmix parameters using bitstream control signals to manage audio rendering.

Segmenting autoencoder layers separates encoding from quantization to prevent cumulative signal loss during high-efficiency audio compression.

A unified messaging system generates text messages using predefined templates and sound input from portable devices.

Intelligent gap filling reconstructs spectral gaps using parametric data within the MDCT domain to preserve high-frequency audio content.

Dynamic spatial parameter limiting stabilizes up-mixing and reduces bandwidth consumption in adaptive audio coding.

Grouping voice data by feature similarity reduces calculation volume while maintaining authentication accuracy for short utterances.

Identifying and suppressing specific neural network nodes activated by altered inputs reduces false recognitions while preserving accuracy for valid data.

Host adjusts voice volume based on detected sub-device count to prevent excessive summation and maintain comfortable listening levels.

A method filters amplitude-modulated radio signals by measuring standardized modulation levels to select appropriate filter configurations.

Automated testing system generates synthetic call flows to evaluate speaker authentication accuracy.

Detects volume level changes in audio communications to flag potential illicit activities without analyzing full content complexity.

Segmented acoustic impulse response synthesis trains lightweight neural networks for efficient audio dereverberation.

A pretrained visual encoder extracts facial expressions into latent codes invariant to identity and view angle.

A decoder determines the percentage of broadband active speech frames to adjust comfort noise data rates during discontinuous transmission phases.

A spectrum smoothing apparatus processes audio signals by dividing spectra into subbands and calculating representative values for each segment.

A variable-speed audio processing method adjusts phase signals across frames to maintain consistent tone and timbre during playback.

Frequency-to-voltage converters transform audio signals into voltage levels for direct comparison against trigger commands.

A speech presence probability method uses normalized signal-to-noise ratio and power level difference parameters to reduce computational complexity.

Phase detection and amplitude attenuation extract center channel information from stereo recordings without converting the signal to monophonic format.

A voice enhancement device resets cumulative histograms based on vehicle state changes to estimate noise components for each frequency.

Dynamic threshold adjustment based on parameter distribution maintains estimation accuracy against noise without manual human raters.

A wearable badge sensor detects physiological performance characteristics to identify emotional states.

A processor generates a residual signal by comparing original and compressed audio samples for transmission.

A symbol-based watermark detection system evaluates signal-to-noise ratios to identify likely symbol values within media streams.

Detects playback device positions to adapt audio signals automatically, resolving system complexity trade-offs.

Phase shifting multi-channel signals minimizes phase differences, preventing gain divergence and maintaining signal integrity during encoding.

A signal processing apparatus restores input signals using learned parameters and weighting coefficients to correct errors between original and restored components.

A song determining method extracts audio from video segments to identify target tracks using matched frame units.