most citedA Review of Deep Learning Techniques for Speech Processing

22 citations · 38 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

Language Guided Visual Question Answering: Elevate Your Multimodal Language Model Using Knowledge-Enriched Prompts

Deepanway Ghosal, Navonil Majumder, Roy Ka-Wei Lee +2

Visual question answering (VQA) is the task of answering questions about an image. The task assumes an understanding of both the image and the question to provide a natural languag…

eess.AS202322 cited

A Review of Deep Learning Techniques for Speech Processing

Ambuj Mehrish, Navonil Majumder, Rishabh Bhardwaj +2

The field of speech processing has undergone a transformative shift with the advent of deep learning. The use of multiple processing layers has enabled the creation of models capab…

cs.SD2023

ADAPTERMIX: Exploring the Efficacy of Mixture of Adapters for Low-Resource TTS Adaptation

Ambuj Mehrish, Abhinav Ramesh Kashyap, Li Yingting +2

There are significant challenges for speaker adaptation in text-to-speech for languages that are not widely spoken or for speakers with accents or dialects that are not well-repres…

eess.AS202315 cited

Text-to-Audio Generation using Instruction-Tuned LLM and Latent Diffusion Model

Deepanway Ghosal, Navonil Majumder, Ambuj Mehrish +1

The immense scale of the recent large language models (LLM) allows many interesting properties, such as, instruction- and chain-of-thought-based fine-tuning, that has significantly…

cs.CL2023

Sentence Embedder Guided Utterance Encoder (SEGUE) for Spoken Language Understanding

Yi Xuan Tan, Navonil Majumder, Soujanya Poria

The pre-trained speech encoder wav2vec 2.0 performs very well on various spoken language understanding (SLU) tasks. However, on many tasks, it trails behind text encoders with text…

cs.CL20231 cited

Evaluating Parameter-Efficient Transfer Learning Approaches on SURE Benchmark for Speech Understanding

Yingting Li, Ambuj Mehrish, Shuai Zhao +5

Fine-tuning is widely used as the default algorithm for transfer learning from pre-trained models. Parameter inefficiency can however arise when, during transfer learning, all the…