Search Results for author:
Found 9 papers, 4 papers with code
Speaker Recognition in the Wild
To understand and evaluate the accuracy of our proposed pipeline, we introduce two metrics: Cluster Purity, and Cluster Uniqueness.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
indic-punct: An automatic punctuation restoration and inverse text normalization framework for Indic languages
Automatic Speech Recognition (ASR) generates text which is most of the times devoid of any punctuation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
Effectiveness of text to speech pseudo labels for forced alignment and cross lingual pretrained models for low resource speech recognition
For a lot of low resource languages the current approaches are still challenging, since in many cases labelled data is not available in open domain.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Is Word Error Rate a good evaluation metric for Speech Recognition in Indic Languages?
We implement our methodology in Hindi which is one of the main languages from Indic context and we think this approach is scalable to other similar languages containing a large character set.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Improving Speech Recognition for Indic Languages using Language Model
We study the effect of applying a language model (LM) on the output of Automatic Speech Recognition (ASR) systems for Indic languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Code Switched and Code Mixed Speech Recognition for Indic languages
The decoding information from a multilingual model is used for language identification and then combined with monolingual models to get an improvement of 50% WER across languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Vakyansh: ASR Toolkit for Low Resource Indic languages
We present Vakyansh, an end to end toolkit for Speech Recognition in Indic languages.
Toxicity Detection for Indic Multilingual Social Media Content
We also observed an increase in the performance by adding transliterated data.
CLSRIL-23: Cross Lingual Speech Representations for Indic Languages
We present a CLSRIL-23, a self supervised learning based audio pre-trained model which learns cross lingual speech representations from raw audio across 23 Indic languages.
