Speech Analysis TRIZ Cases

Structured hierarchies organize VoIP contextual information to resolve the contradiction between enhanced calling features and transfer efficiency.

Dividing frequency-lowered signal frames into fading sub-frames prevents duration extension and interference with other voice signals.

A digital audio signal processing method calculates a leading energy coefficient for sub-blocks preceding an attack to verify pre-echo conditions.

A unified transform merges inverse and forward operations to process audio data directly in the frequency domain.

Audio decoding apparatus selects specific decoding units based on transmitted signal classification information for optimal processing.

A mobile communication device processes distorted audio signals using compact spectra prototypes to remove noise components efficiently.

A cockpit audio system calculates pilot head position using sound wave propagation time to measure vigilance levels.

A noise reduction apparatus uses reference signals to subtract sudden sounds from voice inputs.

An auxiliary device generates artificial noise signals to enable real-time updates of suppression parameters in information processing systems.

Segmenting detection into low and high power stages reduces energy consumption while maintaining reliable media identification accuracy.

A presence system generates audio fingerprints to authenticate users in voice activated networks.

An audio coding device corrects envelope information based on tone signal frequency differences to prevent adjacent peaks in decoded high-band signals.

Phase-matching sampling points between overlapping frequency-lowered signal frames reduces signal distortion caused by phase mismatching.

A data processing method generates compensation packets from adjacent data to replace lost voice packets in transmission streams.

Segmenting lost signal units into groups applies distinct concealment algorithms to balance power consumption against compensation effectiveness.

A speech coding system extracts audio features to generate an enhancement signal that mixes with decoded audio for improved frequency band coverage.

Asymmetric windowing offsets unequal overlaps via unevenly weighted smoothing, reducing audio artifacts in multichannel decoding.

Processor evaluates microphone signal combinations using signal-to-noise ratios to resolve trade-offs between speech quality and processing complexity.

Neural network voiceprint extractor captures holographic speaker features from brief audio clips.

A hybrid u-net system processes voice signals through time and frequency domains to cancel noise components.

Segmented audio cancellation processes resolve noise suppression versus transparency trade-offs while enabling remote rendering.

Extraction unit isolates specific sound sources from ambisonic microphone arrays to convert directional narration into omnidirectional audio data.

Integrating input device frequency response with voice data enables accurate speaker verification across diverse recording hardware.

A machine learning model processes multiple microphone signals to isolate user speech in the time domain.

A real-time audio source separation technique leveraging pre-computed reference data to isolate speech signals from mixed input streams.

Pitch-synchronous timbre vectors replace LPC coefficients to capture spectral details accurately, enabling CD-quality speech reproduction at low bandwidth.

Modifying spectral tilt via a dynamic noise controller prevents noise gating while maintaining speech quality.

A speech enhancement system transforms audio frames through coarse and fine frequency domain steps to reduce processing latency.

Correlates microphone audio with IMU orientation data using machine learning models to identify sound sources while managing battery consumption.

Encoder extracts spectral shape parameters to reconstruct high-band audio signals, reducing transmission bits while maintaining accuracy.

Transforming acoustic signals into the frequency domain enables precise impact location determination even under low signal-to-noise ratios.

Motion sensors detect user movement to trigger on-demand presence verification, resolving incomplete viewing data caused by periodic interval checks.

A speech enhancement model processes noisy signals alongside target and interference sound sources to improve clarity.

A mobile terminal registers electronic devices by playing identification sounds and verifying product information through acoustic signals.

Block-based nonlinear processing in a single filterbank reduces computational complexity while maintaining high audio quality for transient signals.

Head-mounted display sensors detect audible and visual behaviors to compute emotional states for real-time feedback.

A multimodal identity recognition system fuses millimeter wave and audio signals to detect liveness features for secure authentication.

A master scale factor band table generates highband signals from lowband audio using pre-determined parameters.

Dividing speech frames into subframes enables selective encoding without fixed codebook contributions to reduce bit rates.

A pitch estimation method computes phase differences between short frame spectra to detect voiced speech without time domain transformation.

Extracting selective acoustic features reduces processing time while maintaining high detection accuracy against replay attacks.

Audio analysis identifies object materials in real environments, resolving the trade-off between detection accuracy and system complexity.

Spectral domain parameterization updates background noise estimates during active audio phases to enable realistic comfort noise synthesis.

A Media Mark embeds identification data into carrier media using perceptual masking and pseudo-random geometric variations.

Audio processing system selects rendering modes based on source spacing to optimize power usage.

Decomposing noise frames into separate low and high band signals using distinct discontinuous transmission mechanisms.

A seat-integrated noise control system uses weight sensors to select stored coefficients for active sound cancellation.

Signal processing means detects input signals from user devices to selectively activate noise suppression algorithms during active periods.

A device displays a visual indicator showing the distance at which an audible signal remains detectable based on environmental audio response characteristics.