2 citations · 2 across the 13 of their papers we have counts for
13 papers
FusDom: Combining In-Domain and Out-of-Domain Knowledge for Continuous Self-Supervised Learning
Ashish Seth, Sreyan Ghosh, S. Umesh +1
Continued pre-training (CP) offers multiple advantages, like target domain adaptation and the potential to exploit the continuous stream of unlabeled data available online. However…
Stable Distillation: Regularizing Continued Pre-training for Low-Resource Automatic Speech Recognition
Ashish Seth, Sreyan Ghosh, S. Umesh +1
Continued self-supervised (SSL) pre-training for adapting existing SSL models to the target domain has shown to be extremely effective for low-resource Automatic Speech Recognition…
The Tag-Team Approach: Leveraging CLS and Language Tagging for Enhancing Multilingual ASR
Kaousheik Jayakumar, Vrunda N. Sukhadia, A Arunkumar +1
Building a multilingual Automated Speech Recognition (ASR) system in a linguistically diverse country like India can be a challenging task due to the differences in scripts and the…
UNFUSED: UNsupervised Finetuning Using SElf supervised Distillation
Ashish Seth, Sreyan Ghosh, S. Umesh +1
In this paper, we introduce UnFuSeD, a novel approach to leverage self-supervised learning and reduce the need for large amounts of labeled data for audio classification. Unlike pr…
Channel-Aware Pretraining of Joint Encoder-Decoder Self-Supervised Model for Telephonic-Speech ASR
Vrunda N. Sukhadia, A. Arunkumar, S. Umesh
This paper proposes a novel technique to obtain better downstream ASR performance from a joint encoder-decoder self-supervised model when trained with speech pooled from two differ…
SLICER: Learning universal audio representations using low-resource self-supervised pre-training
Ashish Seth, Sreyan Ghosh, S. Umesh +1
We present a new Self-Supervised Learning (SSL) approach to pre-train encoders on unlabeled audio data that reduces the need for large amounts of labeled data for audio and speech…
MAST: Multiscale Audio Spectrogram Transformers
Sreyan Ghosh, Ashish Seth, S. Umesh +1
We present Multiscale Audio Spectrogram Transformer (MAST) for audio classification, which brings the concept of multiscale feature hierarchies to the Audio Spectrogram Transformer…
Technology Pipeline for Large Scale Cross-Lingual Dubbing of Lecture Videos into Multiple Indian Languages
Anusha Prakash, Arun Kumar, Ashish Seth +24
Cross-lingual dubbing of lecture videos requires the transcription of the original audio, correction and removal of disfluencies, domain term discovery, text-to-text translation in…
data2vec-aqc: Search for the right Teaching Assistant in the Teacher-Student training setup
Vasista Sai Lodagala, Sreyan Ghosh, S. Umesh
In this paper, we propose a new Self-Supervised Learning (SSL) algorithm called data2vec-aqc, for speech representation learning from unlabeled speech data. Our goal is to improve…
DuDe: Dual-Decoder Multilingual ASR for Indian Languages using Common Label Set
Arunkumar A, Mudit Batra, Umesh S
In a multilingual country like India, multilingual Automatic Speech Recognition (ASR) systems have much scope. Multilingual ASR systems exhibit many advantages like scalability, ma…
CCC-wav2vec 2.0: Clustering aided Cross Contrastive Self-supervised learning of speech representations
Vasista Sai Lodagala, Sreyan Ghosh, S. Umesh
While Self-Supervised Learning has helped reap the benefit of the scale from the available unlabeled data, the learning paradigms are continuously being bettered. We present a new…
Span Classification with Structured Information for Disfluency Detection in Spoken Utterances
Sreyan Ghosh, Sonal Kumar, Yaman Kumar Singla +2
Existing approaches in disfluency detection focus on solving a token-level classification task for identifying and removing disfluencies in text. Moreover, most works focus on leve…
DeToxy: A Large-Scale Multimodal Dataset for Toxicity Classification in Spoken Utterances
Sreyan Ghosh, Samden Lepcha, S Sakshi +2
Toxic speech, also known as hate speech, is regarded as one of the crucial issues plaguing online social media today. Most recent work on toxic speech detection is constrained to t…