Speech Analysis TRIZ Cases

Energy ratio initialization ensures meaningful convergence in multichannel decomposition while user input sorts components.

A bilateral microphone system uses minimum power weighting to reduce noise interference in hearing devices.

Segmented audio objects stream adaptively based on network conditions, resolving bandwidth constraints while maintaining accurate 3D spatial rendering.

A multi-channel acoustic echo canceller adjusts step-size values dynamically using normalized squared cross-correlation metrics.

Dual deep neural networks estimate direct-path signals while a room impulse response filter removes reverberation components from acoustic mixtures.

Extracting independent peak spectra from sound signals enables real-time noise suppression without complex pattern analysis.

Applying modified discrete cosine transform windows to non-speech frames creates zero pad regions that enable perfect reconstruction with reduced frame overlap.

Dynamic template generation adapts to varying ego-noise conditions, reducing processing time while maintaining high suppression performance.

A deep neural network computes clean voice coefficients using per-frequency ratio masks derived from discrete Fourier transform outputs.

A multimodal diagnosis system combines smartphone camera and microphone data to estimate vital signs.

Adaptive noise-canceling circuit detects microphone obstructions by comparing reference and error signals, preventing erroneous anti-noise generation.

Audio processing system applies decibel-based cancelling coefficients to isolate primary user speech from nearby interference.

Variable precision quantization of PARCOR coefficients minimizes linear prediction residual entropy, reducing code amount while maintaining signal fidelity.

A signal processing method generates noise information from degraded signals to suppress noise without pre-stored characteristics.

Interpolation resamples prior frames to maintain post-processing quality during sampling frequency transitions.

A relay station creates communication groups from terminal sound detection requests.

Segmented authentication reduces false matches by filtering generic algorithms with personalized identifier models.

A scalable audio codec allocates bits between frequency bands based on power levels and perceptual modeling.

Offline augmented reality glasses identify individuals using local machine learning models and sensor fusion, eliminating reliance on cloud connectivity.

A masking signal disrupts speech intelligibility by delaying and modulating the original audio, reducing annoyance without increasing loudness.

JIT transcoding computes independent segment context to decouple processing time from video length, eliminating linear delays inherent in batch methods.

A temperament prediction system analyzes audio features to route calls to suitable representatives.

Detecting passenger interest and gaze direction to extract environmental data for detailed feature reconstruction.

A two-level acoustic event detection framework generates a power-probability image from multi-channel tokens to classify specific anomalies.

Audio fingerprinting identifies pre-recorded calls, preventing agent interaction with machines and reducing false positives.

A transmission device inserts attribute information into a metafile to enable selective decoding of encoded audio streams.

Emotion analysis determines caller priority to route users to suitable service channels, resolving inflexible IVR routing bottlenecks.

A watermark signal provider maps time-frequency values to bit shaped functions with temporal overlap for increased redundancy.

Frequency-domain decoding preserves source separation and spatial accuracy while maintaining compatibility with standard two-channel stereo equipment.

Spectrogram analysis of operation sound data identifies abnormal noise sources in image forming apparatuses.

A voice enhancement system detects and dampens passing tire hiss noise to improve speech intelligibility.

Spatial vectors convert audio objects to Higher-Order Ambisonics, resolving backward compatibility conflicts with legacy multi-channel formats.

A matching unit selects audio objects corresponding to visual elements in video signals.

Segmenting input signals into frequency bands allows phase randomization that disrupts feedback loops while maintaining speech audibility.

A computing system divides audio signals into overlapping segments for neural network processing to generate classification scores.

A digital audio processing system adjusts frequency responses to boost speech clarity.

A modified linear prediction analysis window attenuates specific signal points based on inter-channel time differences to enhance encoding precision.

A camera system tracks targets using sound source position signals and object recognition algorithms.

An audio identification system adapts sample length based on signal complexity to generate test fingerprints.

An access terminal dynamically increases silence-frame transmission rates to maintain vocoder activity during communication silence intervals.

Embedded inaudible sound signals enable device microphone detection to verify content playback and ensure full user engagement.

A decoding apparatus selectively inserts spatial information signals into frame headers to enable efficient multi-channel audio reproduction.

A frequency-domain conversion unit generates time-frequency masks to emphasize desired audio signals.

A speech encoder selects between noise-excited and nondifferential pitch prototype coding based on frame energy to optimize bit allocation.

A signal processing method extracts impulse response from audio blocks to modify reverberant content without direct acoustic measurement.

Voice recognition software interprets spoken tags on printed pages to retrieve and print associated documents, eliminating tedious manual interface navigation.