333 citations · 588 across the 48 of their papers we have counts for
8 papers · 1 filter
Mustango: Toward Controllable Text-to-Music Generation
Jan Melechovsky, Zixun Guo, Deepanway Ghosal +3
The quality of the text-to-music models has reached new heights due to recent advancements in diffusion models. The controllability of various musical aspects, however, has barely…
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…
Flacuna: Unleashing the Problem Solving Power of Vicuna using FLAN Fine-Tuning
Deepanway Ghosal, Yew Ken Chia, Navonil Majumder +1
Recently, the release of INSTRUCTEVAL has provided valuable insights into the performance of large language models (LLMs) that utilize encoder-decoder or decoder-only architecture.…
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…
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…
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…
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…
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…