Latest Articles for Speech Recognition

New methods are improving our ability to detect fake speech effectively.

A new method enhances ASR models for individual users using quantisation and adaptation.

New models adapt to improve speech recognition efficiency and responsiveness.

Enhancing Whisper's speech recognition for Vietnamese and other low-resource languages.

This study examines how hearing ability affects speech understanding in noisy settings.

Using k-means clustering to optimize audio data for better model training.

A method to choose the best ASR model based on audio features.

MyST aims to improve children's science learning through virtual tutoring.

A look at M2MeT 2.0 and its impact on meeting transcription.

This study examines how model compression impacts speech recognition in noisy environments.

A new model improves understanding of speech and sounds simultaneously.

Introducing new models for better speech extraction in noisy environments.

Research focuses on improving ASR systems for unsegmented audio.

Examining performance gaps in speech recognition across different genders.

LLMs enhance accuracy and error correction in speech recognition systems.

PP-MeT aims to enhance accuracy in transcribing multi-speaker meetings.

This research presents a model for improving speech clarity across different conditions.

This project aims to improve recognition of Gujarati-English mixed speech.

A new model integrates audio and text for better speech classification.

A new initiative to improve transcription technology for meetings in large rooms.

New methods enhance accuracy in noisy speech recognition using large language models.

This article discusses solutions for speech applications in languages with limited transcribed data.

A new method supports the preservation of at-risk languages through detailed documentation.

A method enhances speech clarity in noisy environments without clear training data.

New methods enhance ASR for underrepresented languages using data from similar languages.

Reborn offers innovative solutions for automatic speech recognition without labeled data.

A look at new models for natural spoken responses.

New methods enhance voice activity and overlap detection in speaker diarization.

Chirp MFCC enhances audio signal representation for better classification and recognition.

Kallaama creates a speech dataset in local languages to aid Senegalese farmers.

A new framework enhances language models by recognizing and responding to different speech styles.

Enhancing ASV systems to recognize children's voices accurately.

Research highlights new models for better audio quality in various environments.

Research highlights the importance of timing over specific speaker features in diarization models.

A look at MONA, a system enhancing silent speech communication.

Research focuses on helping robots better understand speech amidst background noise.

A new benchmark assesses voice recognition systems' performance amidst various disturbances.

AI is improving cochlear implants for better hearing and communication in challenging environments.

This method improves audio separation by combining language descriptions with sound analysis.

Research shows promise in using speech analysis for identifying Parkinson's disease early.