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Found 13 papers, 7 papers with code
IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages
Prior to this work, there was (i) no parallel training data spanning all 22 languages, (ii) no robust benchmarks covering all these languages and containing content relevant to India, and (iii) no existing translation models which support all the 22 scheduled languages of India.
SemEval 2023 Task 6: LegalEval - Understanding Legal Texts
LegalEval task has three sub-tasks: Task-A (Rhetorical Roles Labeling) is about automatically structuring legal documents into semantically coherent units, Task-B (Legal Named Entity Recognition) deals with identifying relevant entities in a legal document and Task-C (Court Judgement Prediction with Explanation) explores the possibility of automatically predicting the outcome of a legal case along with providing an explanation for the prediction.
Named Entity Recognition in Indian court judgments
Identification of named entities from legal texts is an essential building block for developing other legal Artificial Intelligence applications.
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.
Corpus for Automatic Structuring of Legal Documents
In this paper, we introduce a new corpus for structuring legal documents.
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.
Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages
We mine the parallel sentences from the web by combining many corpora, tools, and methods: (a) web-crawled monolingual corpora, (b) document OCR for extracting sentences from scanned documents, (c) multilingual representation models for aligning sentences, and (d) approximate nearest neighbor search for searching in a large collection of sentences.
