Search Results for author:
Found 12 papers, 2 papers with code
Task-Specific Pre-Training and Cross Lingual Transfer for Sentiment Analysis in Dravidian Code-Switched Languages
Sentiment analysis in Code-Mixed languages has garnered a lot of attention in recent years.
Self-training Strategies for Sentiment Analysis: An Empirical Study
Self-training has recently emerged as an economical and efficient technique for developing sentiment analysis models by leveraging a small amount of labeled data and a large amount of unlabeled data.
Intent Classification Using Pre-trained Language Agnostic Embeddings For Low Resource Languages
We perform experiments across three different languages: English, Sinhala, and Tamil each with different data sizes to simulate high, medium, and low resource scenarios.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Intent Recognition and Unsupervised Slot Identification for Low Resourced Spoken Dialog Systems
We build a word-free natural language understanding module that does intent recognition and slot identification from these phonetic transcription.
Unsupervised Self-Training for Sentiment Analysis of Code-Switched Data
We propose a general framework called Unsupervised Self-Training and show its applications for the specific use case of sentiment analysis of code-switched data.
Task-Specific Pre-Training and Cross Lingual Transfer for Code-Switched Data
Using task-specific pre-training and leveraging cross-lingual transfer are two of the most popular ways to handle code-switched data.
Acoustics Based Intent Recognition Using Discovered Phonetic Units for Low Resource Languages
With the aim of aiding development of spoken dialog systems in low resourced languages, we propose a novel acoustics based intent recognition system that uses discovered phonetic units for intent classification.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Mere account mein kitna balance hai? -- On building voice enabled Banking Services for Multilingual Communities
Tremendous progress in speech and language processing has brought language technologies closer to daily human life.
A Resource for Computational Experiments on Mapudungun
We present a resource for computational experiments on Mapudungun, a polysynthetic indigenous language spoken in Chile with upwards of 200 thousand speakers.
Disentangling Speech and Non-Speech Components for Building Robust Acoustic Models from Found Data
We show that the constraints on the latent space of a VAE can be in-fact used to separate speech and music, independent of the language of the speech.
A Survey of Code-switched Speech and Language Processing
Code-switching, the alternation of languages within a conversation or utterance, is a common communicative phenomenon that occurs in multilingual communities across the world.
