---
title: "Jointly Improving Dialect Identification and ASR in Indian Languages using Multimodal Feature Fusion — Stuff That Spins"
description: "arXiv:2607.02862v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) and Dialect Identification (DID) are crucial for Indian languages, many of w…"
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date: "2026-07-07T04:00:00+00:00"
modified: "2026-07-07T06:04:38.339176+00:00"
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# Jointly Improving Dialect Identification and ASR in Indian Languages using Multimodal Feature Fusion

**Source:** Unknown  
**Published:** July 7, 2026  
**Original:** https://arxiv.org/abs/2607.02862  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.02862v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) and Dialect Identification (DID) are crucial for Indian languages, many of which are low-resource and exhibit significant dialectal differences. Existing methods often optimize ASR or DID individually, resulting in performance trade-offs. In this work, we propose a multimodal framework that jointly improves ASR and DID. Our method employs a Bottleneck Encoder to extract dialectal features from Conformer-based spee

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