Speech Analysis TRIZ Cases

Smoothing frequency spectrum coefficients during inactive voice phases eliminates bloop artifacts and ensures stable background noise parameters.

System segments game modules and uses voice characteristics to assess user well-being, resolving complexity trade-offs in real-time personalized gaming.

A hearing system calculates gains from local and remote microphone signals to enhance speech output.

A processing system updates event confidence levels from user messages to tailor information dissemination.

A multi-band signal processor applies separate update rates to frequency bands for optimized spectral analysis.

A machine learning model converts in-ear audio signals into compensated output using dual microphone inputs.

Filtering low frequency signal portions to emphasize predetermined intervals improves perceived loudness and sharpness in reconstructed speech signals.

An audio classification device extracts section features and integrates them to identify moving image events.

Embeds identity watermarks in audio feeds by modulating energy levels at specific frequencies to identify human assessors.

Phase enhancement widens beam pattern nulls to improve directionality without increasing sensor element count or hardware costs.

A unified codec apparatus selects between speech and audio encoding modules based on input signal characteristics.

Insertion unit mixes audio signals with downmix streams and modifies metadata to maintain spatial diversity while avoiding audible artifacts.

Encoder aligns multi-channel audio via identical timestamps, preventing quality degradation during re-encoding.

A bit stream generation method identifies unrequired sections in tactile signal transmission and inserts additional information into these gaps.

Segments processing into down-mixing and rendering stages to lower filtering calculations while maintaining 3D spatial information.

Modifying LPC synthesis filter excitation signals reduces power and spectral fluctuations, eliminating swirling artifacts in stationary background noise.

Computing local gradients characterizes spectrogram neighborhoods, reducing pitch shift distortion impact on energy ratios.

A Volterra filter estimates nonlinear acoustic echo signals using a Multi-Tap Least Squares estimator for dynamic factor adjustment.

A two-stage neural network system processes speech signals to suppress acoustic interference and restore natural audio quality.

Audio processing apparatus separates overlapping mono-channel signals via spectral filtering and time scaling, reducing energetic masking effects.

Parametric upmixing reconstructs channel subsets to enable dialog enhancement, avoiding full decoding complexity.

A flexible renderer adapts audio signals to varying speaker configurations.

A signal processing apparatus groups source signals to enable unified control and independent transmission of mix data.

Dual omnidirectional microphone arrays generate virtual microphones with dissimilar speech responses to improve voice activity detection accuracy.

A state estimating apparatus isolates transmitting-end voice from mixed telephone signals using non-transmission band power analysis.

Diffusion model dequantizes discrete latent vectors to continuous forms, restoring high-fidelity speech from low-bitrate compressed data.

Bitstream carries sparseness metadata to resolve artistic intent loss during compression, ensuring consistent playback across speaker configurations.

Spatial clustering and metadata enable accurate object reconstruction while maintaining legacy decoder compatibility.

A voice vector framework authenticates user interactions by extracting attributes from audio data and applying dynamic classifiers to generate verification scores.

Segmenting voice and ambience channels with embedded spatial metadata resolves device rotation contradictions while maintaining accurate spatial presentation.

Predicts excitation signals and spectral envelopes to synthesize high-frequency bands from decoded audio data.

A speech decoding apparatus adds controlled noise to higher frequency bands of decoded signals.

An audio decoder applies dynamic downmixing by selecting frequency or time domain processing based on channel contribution.

Asymmetric two-microphone arrays calculate energy transfer functions to generate noise reduced audio signals from sound received by distinct microphone positions.

A voice activity detector analyzes feed-forward and error microphone signals to identify user speech in ear-mounted playback devices.

Vertically-stacked directional microphones capture sound source location data for spatial audio rendering.

A vocoder transcodes MELP encoded data between speech frame rates using time interpolation and quantization.

A surround generation apparatus separates stereo signals into high and low correlation components to create spatial audio output.

Audio watermarking embeds data by modifying signal correlation through amplitude and magnitude adjustments, minimizing perceptible distortion during extraction.

A multi-lingual auction data rendering system segments base language fields from translatable entries to serve reader preferences.

A voice correction device adjusts acoustic levels using real-time user response detection to enhance audibility.

Analyzing audio amplitude and energy distribution identifies blocked sound reception holes, enabling alternative collection modes.

Variable coefficient tables adapt to input power spectra, resolving fixed envelope limitations that degrade music clarity and accuracy.

A voiceprint registration system generates user models using text-related training methods and stores them in a database.

An anomaly notification system detects sounds and measures activity levels to identify specific events.

Audio-visual modulation model extracts cross-modal attention features to predict activities in dark video streams.

Clustering fraudster voice prints into representative groups reduces processing latency and improves real-time detection accuracy.