22 citations · 44 across the 20 of their papers we have counts for
5 papers · 1 filter
DART: Disentanglement of Accent and Speaker Representation in Multispeaker Text-to-Speech
Jan Melechovsky, Ambuj Mehrish, Berrak Sisman +1
Recent advancements in Text-to-Speech (TTS) systems have enabled the generation of natural and expressive speech from textual input. Accented TTS aims to enhance user experience by…
Accent Conversion in Text-To-Speech Using Multi-Level VAE and Adversarial Training
Jan Melechovsky, Ambuj Mehrish, Berrak Sisman +1
With rapid globalization, the need to build inclusive and representative speech technology cannot be overstated. Accent is an important aspect of speech that needs to be taken into…
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…
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…
Accented Text-to-Speech Synthesis with a Conditional Variational Autoencoder
Jan Melechovsky, Ambuj Mehrish, Berrak Sisman +1
Accent plays a significant role in speech communication, influencing one's capability to understand as well as conveying a person's identity. This paper introduces a novel and effi…