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References

[Yes]

Yesno. URL: http://www.openslr.org/1/.

[ABD+20]

Rosana Ardila, Megan Branson, Kelly Davis, Michael Henretty, Michael Kohler, Josh Meyer, Reuben Morais, Lindsay Saunders, Francis M. Tyers, and Gregor Weber. Common voice: a massively-multilingual speech corpus. 2020. arXiv:1912.06670.

[BZMA20]

Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, and Michael Auli. Wav2vec 2.0: a framework for self-supervised learning of speech representations. 2020. arXiv:2006.11477.

[BBL+08]

Carlos Busso, Murtaza Bulut, Chi-Chun Lee, Abe Kazemzadeh, Emily Mower Provost, Samuel Kim, Jeannette Chang, Sungbok Lee, and Shrikanth Narayanan. Iemocap: interactive emotional dyadic motion capture database. Language Resources and Evaluation, 42:335–359, 12 2008. doi:10.1007/s10579-008-9076-6.

[Cap69]

Jack Capon. High-resolution frequency-wavenumber spectrum analysis. Proceedings of the IEEE, 57(8):1408–1418, 1969.

[CDiGangiB+21]

Roldano Cattoni, Mattia Antonino Di Gangi, Luisa Bentivogli, Matteo Negri, and Marco Turchi. Must-c: a multilingual corpus for end-to-end speech translation. Computer Speech & Language, 66:101155, 2021. URL: https://www.sciencedirect.com/science/article/pii/S0885230820300887, doi:https://doi.org/10.1016/j.csl.2020.101155.

[CCW+21]

Guoguo Chen, Shuzhou Chai, Guanbo Wang, Jiayu Du, Wei-Qiang Zhang, Chao Weng, Dan Su, Daniel Povey, Jan Trmal, Junbo Zhang, Mingjie Jin, Sanjeev Khudanpur, Shinji Watanabe, Shuaijiang Zhao, Wei Zou, Xiangang Li, Xuchen Yao, Yongqing Wang, Yujun Wang, Zhao You, and Zhiyong Yan. Gigaspeech: an evolving, multi-domain asr corpus with 10,000 hours of transcribed audio. In Proc. Interspeech 2021. 2021.

[CWC+22]

Sanyuan Chen, Chengyi Wang, Zhengyang Chen, Yu Wu, Shujie Liu, Zhuo Chen, Jinyu Li, Naoyuki Kanda, Takuya Yoshioka, Xiong Xiao, and others. Wavlm: large-scale self-supervised pre-training for full stack speech processing. IEEE Journal of Selected Topics in Signal Processing, 16(6):1505–1518, 2022.

[CPS16]

Ronan Collobert, Christian Puhrsch, and Gabriel Synnaeve. Wav2letter: an end-to-end convnet-based speech recognition system. 2016. arXiv:1609.03193.

[CBC+20]

Alexis Conneau, Alexei Baevski, Ronan Collobert, Abdelrahman Mohamed, and Michael Auli. Unsupervised cross-lingual representation learning for speech recognition. 2020. arXiv:2006.13979.

[CPC+20]

Joris Cosentino, Manuel Pariente, Samuele Cornell, Antoine Deleforge, and Emmanuel Vincent. Librimix: an open-source dataset for generalizable speech separation. 2020. arXiv:2005.11262.

[CSB+18]

Alice Coucke, Alaa Saade, Adrien Ball, Théodore Bluche, Alexandre Caulier, David Leroy, Clément Doumouro, Thibault Gisselbrecht, Francesco Caltagirone, Thibaut Lavril, and others. Snips voice platform: an embedded spoken language understanding system for private-by-design voice interfaces. arXiv preprint arXiv:1805.10190, 2018.

[Defossez21]

Alexandre Défossez. Hybrid spectrogram and waveform source separation. In Proceedings of the ISMIR 2021 Workshop on Music Source Separation. 2021.

[GKRR14]

Mark John Francis Gales, Kate Knill, Anton Ragni, and Shakti Prasad Rath. Speech recognition and keyword spotting for low-resource languages: babel project research at cued. In SLTU. 2014.

[GBP+14]

Pegah Ghahremani, Bagher BabaAli, Daniel Povey, Korbinian Riedhammer, Jan Trmal, and Sanjeev Khudanpur. A pitch extraction algorithm tuned for automatic speech recognition. In 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), volume, 2494–2498. 2014. doi:10.1109/ICASSP.2014.6854049.

[Gra12]

Alex Graves. Sequence transduction with recurrent neural networks. 2012. arXiv:1211.3711.

[GL83]

D. Griffin and Jae Lim. Signal estimation from modified short-time fourier transform. In ICASSP '83. IEEE International Conference on Acoustics, Speech, and Signal Processing, volume 8, 804–807. 1983. doi:10.1109/ICASSP.1983.1172092.

[GQC+20]

Anmol Gulati, James Qin, Chung-Cheng Chiu, Niki Parmar, Yu Zhang, Jiahui Yu, Wei Han, Shibo Wang, Zhengdong Zhang, Yonghui Wu, and Ruoming Pang. Conformer: convolution-augmented transformer for speech recognition. 2020. arXiv:2005.08100.

[HCC+14]

Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, and Andrew Y. Ng. Deep speech: scaling up end-to-end speech recognition. 2014. arXiv:1412.5567.

[HIA+17]

Takuya Higuchi, Nobutaka Ito, Shoko Araki, Takuya Yoshioka, Marc Delcroix, and Tomohiro Nakatani. Online mvdr beamformer based on complex gaussian mixture model with spatial prior for noise robust asr. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 25(4):780–793, 2017.

[HIYN16]

Takuya Higuchi, Nobutaka Ito, Takuya Yoshioka, and Tomohiro Nakatani. Robust mvdr beamforming using time-frequency masks for online/offline asr in noise. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 5210–5214. IEEE, 2016.

[HBT+21]

Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed. Hubert: self-supervised speech representation learning by masked prediction of hidden units. 2021. arXiv:2106.07447.

[IJ17]

Keith Ito and Linda Johnson. The lj speech dataset. https://keithito.com/LJ-Speech-Dataset/, 2017.

[KPL+22]

Jacob Kahn, Vineel Pratap, Tatiana Likhomanenko, Qiantong Xu, Awni Hannun, Jeff Cai, Paden Tomasello, Ann Lee, Edouard Grave, Gilad Avidov, and others. Flashlight: enabling innovation in tools for machine learning. arXiv preprint arXiv:2201.12465, 2022.

[KES+18a]

Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aaron van den Oord, Sander Dieleman, and Koray Kavukcuoglu. Efficient neural audio synthesis. 2018. arXiv:1802.08435.

[KES+18b]

Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aäron van den Oord, Sander Dieleman, and Koray Kavukcuoglu. Efficient neural audio synthesis. CoRR, 2018. URL: http://arxiv.org/abs/1802.08435, arXiv:1802.08435.

[KPPK15]

Tom Ko, Vijayaditya Peddinti, Daniel Povey, and Sanjeev Khudanpur. Audio augmentation for speech recognition. In Proc. Interspeech 2015, 3586–3589. 2015. doi:10.21437/Interspeech.2015-711.

[KBV03]

John Kominek, Alan W Black, and Ver Ver. Cmu arctic databases for speech synthesis. Technical Report, 2003.

[LRI+19]

Loren Lugosch, Mirco Ravanelli, Patrick Ignoto, Vikrant Singh Tomar, and Yoshua Bengio. Speech model pre-training for end-to-end spoken language understanding. In Gernot Kubin and Zdravko Kacic, editors, Proc. of Interspeech, 814–818. 2019.

[LM19]

Yi Luo and Nima Mesgarani. Conv-tasnet: surpassing ideal time–frequency magnitude masking for speech separation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 27(8):1256–1266, Aug 2019. URL: http://dx.doi.org/10.1109/TASLP.2019.2915167, doi:10.1109/taslp.2019.2915167.

[MRFB+15]

Xavier Anguera Miro, Luis Javier Rodriguez-Fuentes, Andi Buzo, Florian Metze, Igor Szoke, and Mikel Peñagarikano. Quesst2014: evaluating query-by-example speech search in a zero-resource setting with real-life queries. 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 5833–5837, 2015.

[MPG29]

RV Mises and Hilda Pollaczek-Geiringer. Praktische verfahren der gleichungsauflösung. ZAMM-Journal of Applied Mathematics and Mechanics/Zeitschrift für Angewandte Mathematik und Mechanik, 9(1):58–77, 1929.

[NCZ17]

Arsha Nagrani, Joon Son Chung, and Andrew Zisserman. Voxceleb: a large-scale speaker identification dataset. arXiv preprint arXiv:1706.08612, 2017.

[PCPK15]

Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur. Librispeech: an asr corpus based on public domain audio books. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), volume, 5206–5210. 2015. doi:10.1109/ICASSP.2015.7178964.

[PCZ+19]

Daniel S. Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D. Cubuk, and Quoc V. Le. Specaugment: a simple data augmentation method for automatic speech recognition. Interspeech 2019, Sep 2019. URL: http://dx.doi.org/10.21437/Interspeech.2019-2680, doi:10.21437/interspeech.2019-2680.

[PBS13]

Nathanaël Perraudin, Peter Balazs, and Peter L. Søndergaard. A fast griffin-lim algorithm. In 2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, volume, 1–4. 2013. doi:10.1109/WASPAA.2013.6701851.

[PXS+20]

Vineel Pratap, Qiantong Xu, Anuroop Sriram, Gabriel Synnaeve, and Ronan Collobert. Mls: a large-scale multilingual dataset for speech research. Interspeech 2020, Oct 2020. URL: http://dx.doi.org/10.21437/Interspeech.2020-2826, doi:10.21437/interspeech.2020-2826.

[RLStoter+19]

Zafar Rafii, Antoine Liutkus, Fabian-Robert Stöter, Stylianos Ioannis Mimilakis, and Rachel Bittner. MUSDB18-HQ - an uncompressed version of musdb18. December 2019. URL: https://doi.org/10.5281/zenodo.3338373, doi:10.5281/zenodo.3338373.

[RDelegliseEsteve12]

Anthony Rousseau, Paul Deléglise, and Yannick Estève. Ted-lium: an automatic speech recognition dedicated corpus. In Conference on Language Resources and Evaluation (LREC), 125–129. 2012.

[SY18]

Seyyed Saeed Sarfjoo and Junichi Yamagishi. Device recorded vctk (small subset version). 2018.

[SPW+18]

Jonathan Shen, Ruoming Pang, Ron J Weiss, Mike Schuster, Navdeep Jaitly, Zongheng Yang, Zhifeng Chen, Yu Zhang, Yuxuan Wang, Rj Skerrv-Ryan, and others. Natural tts synthesis by conditioning wavenet on mel spectrogram predictions. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4779–4783. IEEE, 2018.

[SWW+21]

Yangyang Shi, Yongqiang Wang, Chunyang Wu, Ching-Feng Yeh, Julian Chan, Frank Zhang, Duc Le, and Mike Seltzer. Emformer: efficient memory transformer based acoustic model for low latency streaming speech recognition. In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 6783–6787. 2021.

[SWW+22]

Yangyang Shi, Chunyang Wu, Dilin Wang, Alex Xiao, Jay Mahadeokar, Xiaohui Zhang, Chunxi Liu, Ke Li, Yuan Shangguan, Varun Nagaraja, Ozlem Kalinli, and Mike Seltzer. Streaming transformer transducer based speech recognition using non-causal convolution. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), volume, 8277–8281. 2022. doi:10.1109/ICASSP43922.2022.9747706.

[Smi20]

Julius O. Smith. Digital audio resampling home page "theory of ideal bandlimited interpolation" section. September 2020. URL: https://ccrma.stanford.edu/~jos/resample/Theory_Ideal_Bandlimited_Interpolation.html.

[SBA09]

Mehrez Souden, Jacob Benesty, and Sofiene Affes. On optimal frequency-domain multichannel linear filtering for noise reduction. In IEEE Transactions on audio, speech, and language processing, volume 18, 260–276. IEEE, 2009.

[SWT+22]

Sangeeta Srivastava, Yun Wang, Andros Tjandra, Anurag Kumar, Chunxi Liu, Kritika Singh, and Yatharth Saraf. Conformer-based self-supervised learning for non-speech audio tasks. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), volume, 8862–8866. 2022. doi:10.1109/ICASSP43922.2022.9746490.

[TEC01]

George Tzanetakis, Georg Essl, and Perry Cook. Automatic musical genre classification of audio signals. 2001. URL: http://ismir2001.ismir.net/pdf/tzanetakis.pdf.

[WRiviereL+21]

Changhan Wang, Morgane Rivière, Ann Lee, Anne Wu, Chaitanya Talnikar, Daniel Haziza, Mary Williamson, Juan Miguel Pino, and Emmanuel Dupoux. Voxpopuli: A large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation. CoRR, 2021. URL: https://arxiv.org/abs/2101.00390, arXiv:2101.00390.

[Wei98]

R.L. Weide. The carnegie mellon pronuncing dictionary. 1998. URL: http://www.speech.cs.cmu.edu/cgi-bin/cmudict.

[YVM19]

Junichi Yamagishi, Christophe Veaux, and Kirsten MacDonald. CSTR VCTK Corpus: english multi-speaker corpus for CSTR voice cloning toolkit (version 0.92). 2019. doi:10.7488/ds/2645.

[ZDC+19]

Heiga Zen, Viet-Trung Dang, Robert A. J. Clark, Yu Zhang, Ron J. Weiss, Ye Jia, Z. Chen, and Yonghui Wu. Libritts: a corpus derived from librispeech for text-to-speech. ArXiv, 2019.

[BrianMcFeeColinRaffelDawenLiang+15]

Brian McFee, Colin Raffel, Dawen Liang, Daniel P.W. Ellis, Matt McVicar, Eric Battenberg, and Oriol Nieto. Librosa: Audio and Music Signal Analysis in Python. In Kathryn Huff and James Bergstra, editors, Proceedings of the 14th Python in Science Conference, 18 – 24. 2015. doi:10.25080/Majora-7b98e3ed-003.

[KahnRiviereZheng+20]

J. Kahn, M. Rivière, W. Zheng, E. Kharitonov, Q. Xu, P. E. Mazaré, J. Karadayi, V. Liptchinsky, R. Collobert, C. Fuegen, T. Likhomanenko, G. Synnaeve, A. Joulin, A. Mohamed, and E. Dupoux. Libri-light: a benchmark for asr with limited or no supervision. In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 7669–7673. 2020. https://github.com/facebookresearch/libri-light.

[Warden18]

P. Warden. Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition. ArXiv e-prints, April 2018. URL: https://arxiv.org/abs/1804.03209, arXiv:1804.03209.

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