33 citations · 64 across the 17 of their papers we have counts for
8 papers · 1 filter
Data augmentation using prosody and false starts to recognize non-native children's speech
Hemant Kathania, Mittul Singh, Tamás Grósz +1
This paper describes AaltoASR's speech recognition system for the INTERSPEECH 2020 shared task on Automatic Speech Recognition (ASR) for non-native children's speech. The task is t…
FinChat: Corpus and evaluation setup for Finnish chat conversations on everyday topics
Katri Leino, Juho Leinonen, Mittul Singh +2
Creating open-domain chatbots requires large amounts of conversational data and related benchmark tasks to evaluate them. Standardized evaluation tasks are crucial for creating aut…
Aalto's End-to-End DNN systems for the INTERSPEECH 2020 Computational Paralinguistics Challenge
Tamás Grósz, Mittul Singh, Sudarsana Reddy Kadiri +2
End-to-end neural network models (E2E) have shown significant performance benefits on different INTERSPEECH ComParE tasks. Prior work has applied either a single instance of an E2E…
Effects of Language Relatedness for Cross-lingual Transfer Learning in Character-Based Language Models
Mittul Singh, Peter Smit, Sami Virpioja +1
Character-based Neural Network Language Models (NNLM) have the advantage of smaller vocabulary and thus faster training times in comparison to NNLMs based on multi-character units.…
Subword RNNLM Approximations for Out-Of-Vocabulary Keyword Search
Mittul Singh, Sami Virpioja, Peter Smit +1
In spoken Keyword Search, the query may contain out-of-vocabulary (OOV) words not observed when training the speech recognition system. Using subword language models (LMs) in the f…
Transfer learning and subword sampling for asymmetric-resource one-to-many neural translation
Stig-Arne Grönroos, Sami Virpioja, Mikko Kurimo
There are several approaches for improving neural machine translation for low-resource languages: Monolingual data can be exploited via pretraining or data augmentation; Parallel c…