Development of Supervised Speaker Diarization System Based on the PyAnnote Audio Processing Library [PDF]
Sensors, 2023 Diarization is an important task when work with audiodata is executed, as it provides a solution to the problem related to the need of dividing one analyzed call recording into several speech recordings, each of which belongs to one speaker.
Volodymyr Khoma +3 more
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Real-time multilingual speech recognition and speaker diarization system based on Whisper segmentation [PDF]
PeerJ Computer ScienceThis research presents the development of a cutting-edge real-time multilingual speech recognition and speaker diarization system that leverages OpenAI’s Whisper model. The system specifically addresses the challenges of automatic speech recognition (ASR)
Ke-Ming Lyu +2 more
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TSUP Speaker Diarization System for Conversational Short-phrase Speaker Diarization Challenge [PDF]
2022 13th International Symposium on Chinese Spoken Language Processing (ISCSLP), 2022 This paper describes the TSUP team's submission to the ISCSLP 2022 conversational short-phrase speaker diarization (CSSD) challenge which particularly focuses on short-phrase conversations with a new evaluation metric called conversational diarization error rate (CDER).
Bowen Pang 0002 +7 more
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An enhanced deep learning approach for speaker diarization using TitaNet, MarbelNet and time delay network [PDF]
Scientific ReportsSpeaker diarization, identifying “who spoke when,” plays a vital role in speech transcription, supervised fine-tuning of large language models, conversational AI, and audio content analysis by providing labeled speaker segments.
Muzamil Ahmed +5 more
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Automatic speaker diarization for natural conversation analysis in autism clinical trials [PDF]
Scientific Reports, 2023 Challenges in social communication is one of the core symptom domains in autism spectrum disorder (ASD). Novel therapies are under development to help individuals with these challenges, however the ability to show a benefit is dependent on a sensitive ...
James O’Sullivan +14 more
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Multisensory Fusion for Unsupervised Spatiotemporal Speaker Diarization [PDF]
SensorsSpeaker diarization consists of answering the question of “who spoke when” in audio recordings. In meeting scenarios, the task of labeling audio with the corresponding speaker identities can be further assisted by the exploitation of spatial features ...
Paris Xylogiannis +3 more
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Speaker diarization system using HXLPS and deep neural network
Alexandria Engineering Journal, 2018 In general, speaker diarization is defined as the process of segmenting the input speech signal and grouped the homogenous regions with regard to the speaker identity. The main idea behind this system is that it is able to discriminate the speaker signal
V. Subba Ramaiah, R. Rajeswara Rao
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Bayes factor based speaker segmentation for speaker diarization [PDF]
Interspeech 2010, 2010 This paper proposes the use of the Bayes Factor as a distance metric for speaker segmentation within a speaker diarization system. The proposed approach uses a pair of constant sized, sliding windows to compute the value of the Bayes Factor between the adjacent windows over the entire audio.
Wang, David +2 more
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Machine Learning-Assisted Speech Analysis for Early Detection of Parkinson’s Disease: A Study on Speaker Diarization and Classification Techniques [PDF]
SensorsParkinson’s disease (PD) is a neurodegenerative disorder characterized by a range of motor and non-motor symptoms. One of the notable non-motor symptoms of PD is the presence of vocal disorders, attributed to the underlying pathophysiological changes in ...
Michele Giuseppe Di Cesare +3 more
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USED: Universal Speaker Extraction and Diarization [PDF]
IEEE Transactions on Audio, Speech and Language ProcessingSpeaker extraction and diarization are two enabling techniques for real-world speech applications. Speaker extraction aims to extract a target speaker's voice from a speech mixture, while speaker diarization demarcates speech segments by speaker, annotating `who spoke when'. Previous studies have typically treated the two tasks independently.
Junyi Ao +8 more
core +7 more sources