Deep learning for speech separation. [PDF]
, 2020 Speech source separation aims to estimate one or more individual sources from mixtures of multiple sound sources, e.g. speech, noise and music. While humans have an innate ability to separate sources in a sound mixture, this is not a trivial task for ...
Zermini, Alfredo
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Brain‐Controlled Augmented Hearing for Spatially Moving Conversations in Multi‐Talker Environments
Advanced ScienceFocusing on a specific conversation amidst multiple interfering talkers is challenging, especially for those with hearing loss. Brain‐controlled assistive hearing devices aim to alleviate this problem by enhancing the attended speech based on the ...
Vishal Choudhari +6 more
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Heterogeneous Separation Consistency Training for Adaptation of Unsupervised Speech Separation
SSRN Electronic Journal, 2022 AbstractRecently, supervised speech separation has made great progress. However, limited by the nature of supervised training, most existing separation methods require ground-truth sources and are trained on synthetic datasets. This ground-truth reliance is problematic, because the ground-truth signals are usually unavailable in real conditions ...
Jiangyu Han, Yanhua Long
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Solving permutations in frequencyy-domain for blind separation of an arbitrary number of speech sources [PDF]
, 2011 Blind separation of speech sources in reverberant environ ments is usually performed in the time-frequency domain, which gives rise to the permutation problem: the different ordering of estimated sources for different frequency components.
Durán Díaz, Iván +3 more
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Self-Remixing: Unsupervised Speech Separation VIA Separation and Remixing
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023 Accepted by ICASSP2023, 5pages, 2figures ...
Kohei Saijo, Tetsuji Ogawa
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Lombard speech synthesis using transfer learning in a Tacotron text-to-speech system
, 2019 Currently, there is increasing interest to use sequence-to-sequence models in text-to-speech (TTS) synthesis with attention like that in Tacotron models.
Bajibabu Bollepalli +5 more
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EURASIP Journal on Audio, Speech, and Music Processing, 2023 In recent years, the speaker-independent, single-channel speech separation problem has made significant progress with the development of deep neural networks (DNNs).
Chunxi Wang, Maoshen Jia, Xinfeng Zhang
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Directed speech separation for automatic speech recognition of long form conversational speech
Interspeech 2022, 2022 Many of the recent advances in speech separation are primarily aimed at synthetic mixtures of short audio utterances with high degrees of overlap. Most of these approaches need an additional stitching step to stitch the separated speech chunks for long form audio.
Rohit Paturi +3 more
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wav2vec2-based Speech Rating System for Children with Speech Sound Disorder
, 2022 The computational resources were provided by Aalto ScienceIT. This work was supported by NordForsk through the funding to Technology-enhanced foreign and second-language learning of Nordic languages, project number 103893.Speaking is a fundamental way of
Getman, Yaroslav +8 more
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Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment
IEEE Open Journal of Engineering in Medicine and Biology, 2021 Goal: Smartphones can be used to passively assess and monitor patients’ speech impairments caused by ailments such as Parkinson’s disease, Traumatic Brain Injury (TBI), Post-Traumatic Stress Disorder (PTSD) and neurodegenerative diseases ...
Apiwat Ditthapron +2 more
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