1 code implementation • 7 Sep 2021 • Mohd Abbas Zaidi, Sathish Indurthi, Beomseok Lee, Nikhil Kumar Lakumarapu, Sangha Kim
Simultaneous neural machine translation(SNMT) models start emitting the target sequence before they have processed the source sequence.
no code implementations • ICASSP 2021 • Sathish Indurthi, Mohd Abbas Zaidi, Nikhil Kumar Lakumarapu, Beomseok Lee, Hyojung Han, Seokchan Ahn, Sangha Kim, Chanwoo Kim, Inchul Hwang
In general, the direct Speech-to-text translation (ST) is jointly trained with Automatic Speech Recognition (ASR), and Machine Translation (MT) tasks.
Ranked #1 on Speech-to-Text Translation on MuST-C EN->DE (using extra training data)
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 29 Dec 2020 • Hyojung Han, Sathish Indurthi, Mohd Abbas Zaidi, Nikhil Kumar Lakumarapu, Beomseok Lee, Sangha Kim, Chanwoo Kim, Inchul Hwang
The current re-translation approaches are based on autoregressive sequence generation models (ReTA), which generate tar-get tokens in the (partial) translation sequentially.
no code implementations • 11 Nov 2019 • Sathish Indurthi, Houjeung Han, Nikhil Kumar Lakumarapu, Beomseok Lee, Insoo Chung, Sangha Kim, Chanwoo Kim
In the meta-learning phase, the parameters of the model are exposed to vast amounts of speech transcripts (e. g., English ASR) and text translations (e. g., English-German MT).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +6
no code implementations • 1 Dec 2015 • Amrita Saha, Sathish Indurthi, Shantanu Godbole, Subendhu Rongali, Vikas C. Raykar
We describe the problem of aggregating the label predictions of diverse classifiers using a class taxonomy.