no code implementations • COLING 2022 • Mana Ihori, Hiroshi Sato, Tomohiro Tanaka, Ryo Masumura
To model the task, we design a novel Japanese multi-perspective document revision dataset that simultaneously handles seven perspectives to improve the readability and clarity of a document.
no code implementations • 23 Apr 2024 • Tsubasa Ochiai, Kazuma Iwamoto, Marc Delcroix, Rintaro Ikeshita, Hiroshi Sato, Shoko Araki, Shigeru Katagiri
To this end, we propose a novel analysis scheme based on the orthogonal projection-based decomposition of SE errors.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 10 Jan 2024 • Kenichi Fujita, Hiroshi Sato, Takanori Ashihara, Hiroki Kanagawa, Marc Delcroix, Takafumi Moriya, Yusuke Ijima
The zero-shot text-to-speech (TTS) method, based on speaker embeddings extracted from reference speech using self-supervised learning (SSL) speech representations, can reproduce speaker characteristics very accurately.
no code implementations • 20 Nov 2023 • Kazuma Iwamoto, Tsubasa Ochiai, Marc Delcroix, Rintaro Ikeshita, Hiroshi Sato, Shoko Araki, Shigeru Katagiri
Jointly training a speech enhancement (SE) front-end and an automatic speech recognition (ASR) back-end has been investigated as a way to mitigate the influence of \emph{processing distortion} generated by single-channel SE on ASR.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 4 Jun 2023 • Ryo Masumura, Naoki Makishima, Taiga Yamane, Yoshihiko Yamazaki, Saki Mizuno, Mana Ihori, Mihiro Uchida, Keita Suzuki, Hiroshi Sato, Tomohiro Tanaka, Akihiko Takashima, Satoshi Suzuki, Takafumi Moriya, Nobukatsu Hojo, Atsushi Ando
Target-speaker ASR systems are a promising way to only transcribe a target speaker's speech by enrolling the target speaker's information.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 25 May 2023 • Takafumi Moriya, Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix, Takanori Ashihara, Kohei Matsuura, Tomohiro Tanaka, Ryo Masumura, Atsunori Ogawa, Taichi Asami
Neural transducer (RNNT)-based target-speaker speech recognition (TS-RNNT) directly transcribes a target speaker's voice from a multi-talker mixture.
no code implementations • 25 May 2023 • Takafumi Moriya, Takanori Ashihara, Hiroshi Sato, Kohei Matsuura, Tomohiro Tanaka, Ryo Masumura
Experiments in three datasets confirm that RNNT trained with our SS approach achieves the best ASR performance.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 24 May 2023 • Hiroshi Sato, Ryo Masumura, Tsubasa Ochiai, Marc Delcroix, Takafumi Moriya, Takanori Ashihara, Kentaro Shinayama, Saki Mizuno, Mana Ihori, Tomohiro Tanaka, Nobukatsu Hojo
In this work, we propose a new SE training criterion that minimizes the distance between clean and enhanced signals in the feature representation of the SSL model to alleviate the mismatch.
1 code implementation • 28 Oct 2022 • Atsushi Ando, Ryo Masumura, Akihiko Takashima, Satoshi Suzuki, Naoki Makishima, Keita Suzuki, Takafumi Moriya, Takanori Ashihara, Hiroshi Sato
This paper investigates the effectiveness and implementation of modality-specific large-scale pre-trained encoders for multimodal sentiment analysis~(MSA).
no code implementations • 9 Sep 2022 • Takafumi Moriya, Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix, Takahiro Shinozaki
We confirm in experiments that our TS-ASR achieves comparable recognition performance with conventional cascade systems in the offline setting, while reducing computation costs and realizing streaming TS-ASR.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 16 Jun 2022 • Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix, Keisuke Kinoshita, Takafumi Moriya, Naoki Makishima, Mana Ihori, Tomohiro Tanaka, Ryo Masumura
Experimental validation reveals the effectiveness of both worst-enrollment target training and SI-loss training to improve robustness against enrollment variations, by increasing speaker discriminability.
no code implementations • 11 Apr 2022 • Marc Delcroix, Keisuke Kinoshita, Tsubasa Ochiai, Katerina Zmolikova, Hiroshi Sato, Tomohiro Nakatani
Target speech extraction (TSE) extracts the speech of a target speaker in a mixture given auxiliary clues characterizing the speaker, such as an enrollment utterance.
no code implementations • 18 Jan 2022 • Kazuma Iwamoto, Tsubasa Ochiai, Marc Delcroix, Rintaro Ikeshita, Hiroshi Sato, Shoko Araki, Shigeru Katagiri
The artifact component is defined as the SE error signal that cannot be represented as a linear combination of speech and noise sources.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 11 Jan 2022 • Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix, Keisuke Kinoshita, Naoyuki Kamo, Takafumi Moriya
To mitigate the degradation, we introduced a rule-based method to switch the ASR input between the enhanced and observed signals, which showed promising results.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 2 Jun 2021 • Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix, Keisuke Kinoshita, Takafumi Moriya, Naoyuki Kamo
', we analyze ASR performance on observed and enhanced speech at various noise and interference conditions, and show that speech enhancement degrades ASR under some conditions even for overlapping speech.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 2 Feb 2021 • Hiroshi Sato, Tsubasa Ochiai, Keisuke Kinoshita, Marc Delcroix, Tomohiro Nakatani, Shoko Araki
Recently an audio-visual target speaker extraction has been proposed that extracts target speech by using complementary audio and visual clues.