activity
20192026
most citedConvolutional Feature Extraction and Neural Arithmetic Logic Units for Stock Prediction

6 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

eess.AS2026

DualTurn: Learning Turn-Taking from Dual-Channel Generative Speech Pretraining

Shangeth Rajaa

Speech-to-speech models handle turn-taking naturally but offer limited support for tool-calling or complex reasoning, while production ASR-LLM-TTS voice pipelines offer these capab…

cs.CL2023

Improving End-to-End SLU performance with Prosodic Attention and Distillation

Shangeth Rajaa

Most End-to-End SLU methods depend on the pretrained ASR or language model features for intent prediction. However, other essential information in speech, such as prosody, is often…

cs.LG2023

Improving Spoken Language Identification with Map-Mix

Shangeth Rajaa, Kriti Anandan, Swaraj Dalmia +2

The pre-trained multi-lingual XLSR model generalizes well for language identification after fine-tuning on unseen languages. However, the performance significantly degrades when th…

cs.CL2022

Skit-S2I: An Indian Accented Speech to Intent dataset

Shangeth Rajaa, Swaraj Dalmia, Kumarmanas Nethil

Conventional conversation assistants extract text transcripts from the speech signal using automatic speech recognition (ASR) and then predict intent from the transcriptions. Using…

eess.AS2021★ 2 cited

Learning Speaker Representation with Semi-supervised Learning approach for Speaker Profiling

Shangeth Rajaa, Pham Van Tung, Chng Eng Siong

Speaker profiling, which aims to estimate speaker characteristics such as age and height, has a wide range of applications inforensics, recommendation systems, etc. In this work, w…

cs.LG2019★ 6 cited

Convolutional Feature Extraction and Neural Arithmetic Logic Units for Stock Prediction

Shangeth Rajaa, Jajati Keshari Sahoo

Stock prediction is a topic undergoing intense study for many years. Finance experts and mathematicians have been working on a way to predict the future stock price so as to decide…