Speech Analysis TRIZ Cases

A processing system generates harmonics from a dominant frequency to create low frequency perception in audio signals.

A dynamic noise reduction system selectively attenuates background noise across frequency bands to enhance speech quality.

A COP packetizing circuit scales bit rates to match encoded audio frame sizes, enabling efficient transmission over isochronous PCM interfaces.

Acoustic control apparatus calculates filter coefficients to direct sound energy toward the driver seat.

Dynamic beam analysis resolves transient noise spectrum estimation errors, ensuring clearer voice output.

Periodic sound extraction on mobile receivers delivers related content automatically while minimizing power consumption and extending battery life.

Decoupling audio and emotion inputs resolves upper face motion limits while reducing training data requirements.

A lossless audio coding method selects between two coding techniques based on the energy quantization index range to optimize bit usage.

Adaptive time compression differentiates voiced speech, unvoiced speech, and silence to reduce artifacts caused by network jitter.

Converts stereo signals to the complex domain using Hilbert transforms and spatial cues.

Encoder aligns target audio channels before frequency-domain transformation, reducing bit usage caused by microphone temporal mismatch.

Pitch-dependent spectral translation shifts narrowband frequency bands to regenerate wideband speech, reducing metallic artefacts from strong harmonics.

A modification algorithm optimizes mutual information between intended and interpreted audio signals to enhance speech clarity.

A voiced degree factor weights high band excitation signals and random noise to synthesize natural audio components.

Upsampling vibration sensor data enables active filtering of structural noise, preserving acoustic clarity without adding device weight.

Adjusting the signal to mask ratio based on encoded and target bitrates stabilizes average bitrate, reducing computational iterations required for convergence.

A frame loss compensation method calculates MDCT coefficients from prior frames to generate an initial signal for audio recovery.

Dynamic mixing of virtual bass harmonics resolves tonal discrepancies while protecting amplifiers from overload.

Critical sampling via MDCT reduces data overhead and improves sound quality during ACELP to TCX mode transitions.

A unified audio coding approach transforms channel-based and object-based inputs into hierarchical spherical harmonic coefficients for scalable processing.

Dual microphone audio processing device determines gain to attenuate background signals.

Encoding apparatus calculates high-frequency code amount to manage bit allocation across subbands.

An adaptive quantization noise filtering method processes decoded audio signals using frequency band signal-to-noise ratios to determine filter gain values.

A non-linear smoothing filter separates audio signals into harmonic and transient components across frequency and time domains.

A dynamic audio layer selection mechanism compares reference and sample signals to generate output data.

A voice activity detector adjusts its threshold based on estimated background noise levels to enhance signal-to-noise ratios.

An information processing device adjusts audio rendering execution timing based on user line-of-sight data to synchronize output with visual content.

A vaping simulation system generates realistic vapor formations using a particle engine and spatial position data.

Segmenting the audio spectrum into independent bands allows selective gain adjustment that suppresses loud breath noises without degrading speech quality.

Segmenting spherical harmonic coefficients into base and enhancement layers balances encoding complexity with high resolution soundfield accuracy.

A multistage deep learning system estimates noise and clean signal power spectra to suppress audio noise in single microphone inputs.

A voice activity detector on the earpiece signal triggers a gain factor derived from microphone noise magnitude to weight the audio output.

A super frame generator combines multiple auxiliary signal frames into a single structure for efficient multichannel audio transmission.

A weighting function determination apparatus combines spectral and positional data to enhance quantization efficiency of linear prediction coding coefficients.

Segmented audio spectrum analysis computes decision metrics to generate robust digital signatures, resolving data rate mismatches in media tracking.

Interpolating quantization noise shapes across TDAC transitions reduces artifacts while maintaining energy compaction during mode switches.

A time-frequency analysis-synthesis framework derives ambience extraction masks from signal correlations to separate primary and ambient audio components.

Neural networks classify acoustic signatures from hard disk drives to detect component failures before data loss occurs.

A communication system modifies input voice signal characteristics to differentiate simultaneous interlocutors.

A time domain noise suppression system calculates gain factors from signal levels to reduce background noise in speech.

A vehicle conversation assist apparatus routes audio signals to diagonal loudspeakers using signal processing delays.

Adapting context states to pitch variations improves coding efficiency without requiring additional side information.

Processor uses direction of arrival estimation to dynamically adjust beamforming weights, removing environmental noise while preserving voice integrity.

A conference system controls speaker output based on detected conversation states to manage voice transmission.

Merges spatially close audio objects into combined groups to lower data transmission amounts while preserving distinguishable sound sources.

A signal processing apparatus computes and smooths correlation coefficients to reduce common noise components in multi-channel acoustic signals.

A neural network classifier determines audio signal loss functions using activation outputs and reference quantization indices.

Controller calculates canceling sound propagation distance and adjusts output levels, preventing noise amplification at the user's ear position.

Dynamic leakage matrices adjust filter coefficients based on vehicle speed, improving stability and convergence speed in active noise control.