Speech Analysis TRIZ Cases

Generative adversarial nets produce 3D mesh vertex sequences from audio features, eliminating frame jitter and ensuring lip synchronization.

Segmenting standardized ADM modules from custom extensions resolves metadata extension difficulty while reducing local file size via cloud storage integration.

A shared Haar transform combined with a type-IV discrete cosine transform creates a fast pipeline architecture.

A temporal convolutional network generates identity embeddings from raw audio waveforms to capture latent speaker states.

A noise suppressing apparatus calculates frequency band gains using signal-to-noise ratios to limit suppression amounts.

Converting impulse response signals to polar coordinates reduces storage requirements.

A bundled multi-rate feedback autoencoder allocates distinct bitrates to reference and predicted audio frames within a single packet.

Convolutional neural networks extract low-band energy characteristics as side information, restoring decoded audio quality despite low bit rate compression.

A format converter generates internal channel signals from MPEG Surround bitstreams to simplify stereo output processing.

Embedding digital watermarks into content signals enables robust identification of media within ambient noise, acoustic reflections, and temporal distortion.

Segmenting the full spectrum into dedicated modules improves low-frequency noise suppression without excessive complexity.

A communication audio detector enables noise suppression only when needed, preserving music quality.

A unified streaming controller manages media playback across multiple content providers through a single interface.

A fast binaural renderer converts object-based audio signals to headphone outputs using hierarchical source clustering and frame-by-frame convolution.

Copying excitation signals bypasses redundant encoding to prevent voice quality degradation from codec tandeming.

A voice signal detection method segments continuous samples into multiple timeframe resolutions to isolate potential abrupt exceptions for further analysis.

A gain-shaping block adjusts sound signal gain using extracted ambient noise data to control timbre in listening environments.

A vowel sensing voice activity detector identifies human speech using spectral harmonicity analysis of audio signals.

A method assigns signs to tonal and noise spectral bins using preceding packet data to generate estimated MDCT coefficients for audio error concealment.

A temporary dictionary stores recipient names and message words to resolve input effort bottlenecks when entering unconventional terms on reduced keyboards.

An in-band modem converts digital data into noise-like signals compatible with speech codecs.

A four-channel audio processing system separates signals for independent frequency division and digital-to-analog conversion across multiple speakers.

Embedding vectors derived from call audio streams detect interconnect bypass fraud, resolving speed and accuracy trade-offs in telecommunication networks.

A neural network dynamically adjusts its detection threshold based on ambient noise components to classify input signals.

Limiting pitch gain in initial subframes reduces error propagation from packet loss while maintaining speech quality.

A formant-sharpening filter adjusts its factor based on average signal-to-noise ratio to enhance speech reconstruction quality.

Dynamic pitch gain attenuation based on past subframe energy preserves signal continuity and reduces sound breaks during frame erasure concealment.

A stereo signal encoder selects residual sub-band encoding based on downmixed and residual energy levels to optimize audio fidelity.

A signal processing apparatus uses a noise decorrelator and residual noise remover to isolate unwanted components from input signals.

A voice activity detector extends active mode duration using adaptive thresholds to distinguish voice signals from background noise.

Partial decoding of enhancement layer data before re-synchronization balances seeking accuracy against processing power load.

Spatially varying weighting functions enhance soundfield quality, resolving multizone redundancy and improving robustness through dynamic compression.

Varying convolution kernel lengths resolve frequency resolution limits in audio separation, improving Source to Distortion Ratio.

A dual-microphone adaptive directionality system separates target voice from ambient noise using sequential filtering stages.

A parameter adjuster modifies rendering coefficients based on object-related parametric information to reduce upmix signal distortions.

Segmenting background noise into core and enhancement layers resolves the contradiction between encoding complexity and reconstruction accuracy.

A microphone array estimates desired speech signals using spatio-temporal distribution of captured audio data.

Automated edge model retraining uses in-situ positive and negative signal generation to eliminate manual data labeling requirements.

A machine learning model merges acoustic echo cancellation with personalized noise suppression using speaker embedding vectors.

Unified speech and audio coding apparatus determines optimal encoding methods to configure fixed-size audio superframes.

A handwashing monitor detects scrubbing motion near a sink faucet outlet to verify proper hygiene protocols.

A pulse information decoder uses a state number to represent pulse positions across multiple audio tracks.

Dual noise shaping filters process speech signals before and after quantization to manipulate signal and coding noise spectra independently.

Gain shape circuitry scales target samples to smooth energy transitions, eliminating artifacts from inter-frame overlap in wireless audio.

A system transforms text-independent voice prints into text-dependent voice prints using captured passphrase audio streams.

Audio downmix apparatus computes eigenvectors of a covariance matrix to generate an auxiliary downmix matrix for flexible channel reproduction.

Assigns priority levels to microphone devices based on historical audio data analysis.

A voice-driven animation system generates lip shapes using a preconfigured pronunciation model library to simplify algorithm processing.

Pitch correction and enhancement filters process speech signals to reduce computational complexity while maintaining auditory fidelity.

Segmenting audio signals allows spatial processing of ambient sounds while protecting speech clarity from distortion.