Speech Analysis TRIZ Cases

A direct and ambience estimator analyzes spatial parametric information to separate audio signal portions from a downmix.

Dynamic confidence threshold adjustment improves voice identification accuracy in noisy environments.

A noise controller uses a loudspeaker and error microphone to generate a silent zone around a listener.

Segmenting audio blocks into groups with embedded time markers eliminates synchronization delays and discontinuities during encoder switching.

An adaptive de-jitter buffer adjusts target length based on packet arrival statistics to manage voice data playback intervals.

A watermarking method groups digital samples by energy values to embed robust identification bits into media files.

Spectral domain weighting filters subband signals to eliminate the timing misalignment caused by traditional time-domain low pass filters.

Eliminating redundant calculations in T-matrix training reduces processor power and memory usage while maintaining speaker identification accuracy.

A decoding apparatus exchanges low and high frequency samples to extend bandwidth.

Adjusting feedback loop gain based on secondary path variations improves stability and noise cancellation performance.

A geometrically aided filter cascade detects artificial noise peaks in audio signals and generates adaptive suppression filters.

Audio devices replace password entry with voice recognition to eliminate memorization burdens while maintaining authentication security.

A biometric recognition system performs initial and re-recognition operations using data collected at different moments.

A sound source separation device estimates a demixing matrix using log-likelihood functions to isolate voice signals from mixed microphone inputs.

Encoding device extracts residual signal components to minimize perceptual distortion while reducing data amount.

Estimate leakage between object and ambience tracks to determine gain values, maintaining user-defined sound ratios despite signal interference.

A speech quality estimator decomposes audio into harmonic and non-harmonic components to compute a ratio indicating user speech clarity.

Psychoacoustic masking modules guide residue coding in scalable audio enhancement layers, resolving low bitrate quality deterioration.

Adaptive attenuation of synthetic residual signals reduces bit rate requirements while preventing audible switching artifacts during playback.

Decodes audio bitstreams using high frequency reconstruction metadata to regenerate signal bands.

Dynamic codebook selection attenuates unwanted noise components in digital speech signals while maintaining high resolution for desired voice components.

Matrix filtering in the sub-band domain processes N-channel sound data into dual-channel binaural output using deconvolved transfer functions.

A quick consent application records agreements using voice signatures and QR code scanning to verify user identity.

A signal splitter groups voice data by positive and negative half periods to omit redundant sign bits in encoded frames.

Segmenting acoustic echo cancellation from deep learning residual suppression reduces computational complexity while maintaining speech clarity.

A multipoint control unit selects specific bit streams to generate output signals without full decoding.

Embedding comfort noise within the media stream reduces network overhead, resolving the trade-off between reliable audio delivery and bandwidth efficiency.

Segmenting audio into base and enhancement layers resolves the trade-off between spatial resolution and bandwidth consumption.

A computer implemented system embeds watermarks in audio frames using multi-level discrete wavelet transform and singular value decomposition.

A signal processing method shifts decoded audio phases using inter-channel phase difference values to reproduce spatial sound characteristics.

Dynamic noise suppression aggressiveness adjustment compensates for rapid gain changes, preventing noticeable noise level fluctuations.

Noise classification separates speech from interference to expand audio bandwidth while preventing audible artifacts and maintaining intelligibility.

Encoder calculates inter-channel correlation to select common or individual coding modes for stereo signals.

L1-norm optimization and auditory masking separate ambisonic signals into sparse subcomponents to reduce spectral distortion in complex sound fields.

A signal processing apparatus shifts decoded audio phases using inter-channel phase difference flags to enhance sound quality.

Gradually decreasing and increasing gain parameters during scene switching suppresses noise while maintaining audio continuity.

A communication apparatus transmits digitized and packetized data directly between heterogeneous networks using a modem.

A noise reduction system applies a dynamic Kalman filter to subtract background noise from primary signals, reducing listener fatigue in noisy environments.

Classifies crowd noise by fusing spectral and time domain features, resolving interference that degrades detection performance.

Dual determination criteria separate background noise from voice distortion noise, resolving accuracy issues where voice signals are incorrectly suppressed.

Segmenting noise suppression into common and individual processing reduces computation while maintaining consistency during speaker switching.

A wearable device processes voice audio via machine learning to identify emotional content and outputs tactile vibration patterns.

Hierarchical audio coding optimizes bit allocation in the improvement layer using perceptual masking thresholds to enhance signal quality.

A speech-based system classifies incoming audio signals to distinguish natural voices from synthesized ones using trained machine learning algorithms.

Audio monitoring devices record noise events and context data to verify user complaints.

Dynamic encoding adapts channel rates to prevent bit waste and mismatched remote audio services.

A security tool combines GPS location data with transaction history to verify user identity via voice confirmation.

A parametric audio decorrelator structure maps downmix signals through linear pre-multipliers to generate decorrelated intermediate signals.

Automated call monitor segments analysis modules to screen calls, reducing manual review time while improving threat detection reliability.