11 citations · 24 across the 9 of their papers we have counts for
9 papers
Deploying Semantic ID-based Generative Retrieval for Large-Scale Podcast Discovery at Spotify
Edoardo D'Amico, Marco De Nadai, Praveen Chandar +41
Podcast listening is often grounded in a set of favorite shows, while listener intent can evolve over time. This combination of stable preferences and changing intent motivates rec…
Synthetic Cross-accent Data Augmentation for Automatic Speech Recognition
Philipp Klumpp, Pooja Chitkara, Leda Sarı +5
The awareness for biased ASR datasets or models has increased notably in recent years. Even for English, despite a vast amount of available training data, systems perform worse for…
Pushing the performances of ASR models on English and Spanish accents
Pooja Chitkara, Morgane Riviere, Jade Copet +2
Speech to text models tend to be trained and evaluated against a single target accent. This is especially true for English for which native speakers from the United States became t…
Improving Data Driven Inverse Text Normalization using Data Augmentation
Laxmi Pandey, Debjyoti Paul, Pooja Chitkara +6
Inverse text normalization (ITN) is used to convert the spoken form output of an automatic speech recognition (ASR) system to a written form. Traditional handcrafted ITN rules can…
Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions
Chunxi Liu, Michael Picheny, Leda Sarı +7
It is well known that many machine learning systems demonstrate bias towards specific groups of individuals. This problem has been studied extensively in the Facial Recognition are…
Accent-Robust Automatic Speech Recognition Using Supervised and Unsupervised Wav2vec Embeddings
Jialu Li, Vimal Manohar, Pooja Chitkara +5
Speech recognition models often obtain degraded performance when tested on speech with unseen accents. Domain-adversarial training (DAT) and multi-task learning (MTL) are two commo…
Using Pause Information for More Accurate Entity Recognition
Sahas Dendukuri, Pooja Chitkara, Joel Ruben Antony Moniz +3
Entity tags in human-machine dialog are integral to natural language understanding (NLU) tasks in conversational assistants. However, current systems struggle to accurately parse s…
Noise Robust Named Entity Understanding for Voice Assistants
Deepak Muralidharan, Joel Ruben Antony Moniz, Sida Gao +21
Named Entity Recognition (NER) and Entity Linking (EL) play an essential role in voice assistant interaction, but are challenging due to the special difficulties associated with sp…
Topic Spotting using Hierarchical Networks with Self Attention
Pooja Chitkara, Ashutosh Modi, Pravalika Avvaru +2
Success of deep learning techniques have renewed the interest in development of dialogue systems. However, current systems struggle to have consistent long term conversations with…