Speech Analysis TRIZ Cases

Persistent voice media storage extends communication range and capacity by buffering data during poor network conditions.

A hearing aid separates speech signals using an own voice detector and talker extraction unit.

A global pulse replacement method searches fixed codebooks using likelihood-estimator vectors to identify optimal codebook vectors.

Spectral flux analysis detects audio transients for graded modification, preventing pumping artifacts and enabling user-controlled listening experiences.

Dynamic threshold adjustment based on context similarity resolves the contradiction between text-independent usability and speaker recognition accuracy.

A voice authentication system compares registered user features against operational speech to confirm identity.

Recurrent neural networks guide nonnegative matrix factorization to capture long-term temporal dependencies, resolving conventional decomposition inaccuracies.

Segmenting HOA coefficients into directional and ambient components reduces bit rates below 128 kbit/s while preserving spatial resolution.

Segmented vector quantization codebooks jointly encode long-term prediction coefficients, reducing bitrate and computational complexity.

Classifies audio media types to apply dereverberation only to speech, preserving music quality.

A location-based access control system modifies device permissions using user activity data.

Locality sensitive hashing accelerates speaker identification by approximating cosine distances, reducing retrieval time while maintaining high accuracy.

A remote noise detector captures background interference near the source and transmits data to a primary device for signal processing.

A pitch enhancement apparatus processes audio signals in shorter time segments using dynamic pitch period detection to maintain energy integrity.

An electronic base in a baby bottle plays music and tracks location, resolving the trade-off between device complexity and motivation capability.

Analog processing via a rotating capacitive sampler eliminates digital FFTs to resolve high power consumption in voice activity detection.

Mixed multivariate probability density functions resolve permutation errors and enhance separation accuracy in noisy environments.

Segmenting baseband and extended signals reduces algorithmic delay in CELP decoders by avoiding sequential MDCT processing.

Differential encoding uses primary channel pitch to encode secondary channel pitch period, resolving low bit rate sound image stability.

A spectral tilt detector signals frame start times to align bandwidth extension calculations with energy shifts.

A binaural rendering apparatus applies a low-pass filter to an audio signal using metadata-based distance information.

Spectral whitening of mid-side signals reduces computational complexity and improves panned signal handling in MDCT stereo encoding.

An adaptable post-filter adjusts weights via learned mappings to resolve non-stationary noise limitations in speech processing.

Audio processing apparatus converts channel-based content to object-based formats using metadata parsing and channel reordering.

A speaker recognition system employs a smaller artificial neural network trained to emulate a larger model using knowledge distillation.

A circuit identifies reference audio segments and searches cached data using cross-correlation to generate pre-compensated frames.

An audio processing method applies enhanced correlation to locate cut positions, eliminating pitch distortion and artifacts during speed variation.

Encoding apparatus extracts location parameters to represent virtual audio object positions within multi-channel speaker layouts.

Segmented filters adjust microphone phase responses through multidimensional parameter optimization, resolving precision-complexity trade-offs.

A speech decoding device generates a compensated excitation signal using learned pitch pulse waveforms from lost frames.

A conference device synchronizes encoding parameters between encoders to maintain signal continuity during participant status changes.

A computing device reduces non-speech portions of sound inputs using a machine learning model to separate speech from noise.

An intelligent alarm system predicts user cognitive states to generate personalized alerts.

Automated smart doorbell applies local quality principles to filter excessive notifications through multi-zone sensitivity adjustment.

A synchronization system embeds unique audio identifiers in high-frequency signals to deliver complementary content on mobile devices.

A stereo audio apparatus separates center and surround channel elements to calculate energy ratios for speech section detection.

Synthesizes a replica signal to cancel near-field noise generated by in-mask alerts, improving speech-to-noise ratios.

An audio processing apparatus extracts main sounds from surrounding signals while suppressing secondary noise.

A neural network model extracts target environment features and transfers them to source acoustic content data.

A wearable audio device sound identification module detects wearer and external speech using multiple microphones.

A hierarchical audio detection system uses lightweight and deep models to screen generated audio clips efficiently.

Estimates time-variant noise spatial covariance matrices using time-frequency-divided observation signals and mask information for acoustic sources.

An application-specific integrated circuit accelerates low-delay modified discrete cosine transform operations using a dedicated hardware accelerator.

A voice authentication system segments input into high and low confidence words to verify speaker identity using similarity scores.

Closed-loop re-decision optimizes bit allocation by comparing amplitude and phase components, reducing perceptually significant distortion at low data rates.

An authentication apparatus converts stored data into sound wave signals for non-contact transmission to user terminals.

Deriving K intermediary channels from M downmixes enables multichannel support without modifying SAOC standards.

An answering machine detection module processes call responses using configurable acoustic parameters to classify recipients.

Decoder modifies inter-channel phase difference parameters based on temporal misalignment values to resolve coding gain reduction in stereo encoding.

Per-user biasing parameters dynamically adjust speaker authentication thresholds, resolving multi-user voice similarity issues while reducing resource usage.