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Found 11 papers, 4 papers with code
PARIKSHA: A Large-Scale Investigation of Human-LLM Evaluator Agreement on Multilingual and Multi-Cultural Data
We find that humans and LLMs agree fairly well in the pairwise setting but the agreement drops for direct assessment evaluation especially for languages such as Bengali and Odia.
Akal Badi ya Bias: An Exploratory Study of Gender Bias in Hindi Language Technology
Existing research in measuring and mitigating gender bias predominantly centers on English, overlooking the intricate challenges posed by non-English languages and the Global South.
MunTTS: A Text-to-Speech System for Mundari
We present MunTTS, an end-to-end text-to-speech (TTS) system specifically for Mundari, a low-resource Indian language of the Austo-Asiatic family.
X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents
We create a new multilingual benchmark, X-RiSAWOZ, by translating the Chinese RiSAWOZ to 4 languages: English, French, Hindi, Korean; and a code-mixed English-Hindi language.
MinUn: Accurate ML Inference on Microcontrollers
Running machine learning inference on tiny devices, known as TinyML, is an emerging research area.
Annotated Speech Corpus for Low Resource Indian Languages: Awadhi, Bhojpuri, Braj and Magahi
In this paper we discuss an in-progress work on the development of a speech corpus for four low-resource Indo-Aryan languages -- Awadhi, Bhojpuri, Braj and Magahi using the field methods of linguistic data collection.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
MAFIA: Machine Learning Acceleration on FPGAs for IoT Applications
Recent breakthroughs in ML have produced new classes of models that allow ML inference to run directly on milliwatt-powered IoT devices.
Multilingual and code-switching ASR challenges for low resource Indian languages
For this purpose, we provide a total of ~600 hours of transcribed speech data, comprising train and test sets, in these languages including two code-switched language pairs, Hindi-English and Bengali-English.
Crowdsourcing Speech Data for Low-Resource Languages from Low-Income Workers
Unfortunately, collecting labelled speech data in any language is an expensive and resource-intensive task.
GesturePod: Enabling On-device Gesture-based Interaction for White Cane Users
Our in-lab study shows that GesturePod achieves 92% gesture recognition accuracy and can help perform common smartphone tasks faster.
Ranked #1 on
Gesture Recognition
on GesturePod
PipeDream: Fast and Efficient Pipeline Parallel DNN Training
PipeDream is a Deep Neural Network(DNN) training system for GPUs that parallelizes computation by pipelining execution across multiple machines.
Distributed, Parallel, and Cluster Computing
