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Found 7 papers, 1 papers with code
SPIRE-SIES: A Spontaneous Indian English Speech Corpus
Transcripts for 23 hours is generated and validated which can serve as a spontaneous speech ASR benchmark.
Speaking rate attention-based duration prediction for speed control TTS
With the advent of high-quality speech synthesis, there is a lot of interest in controlling various prosodic attributes of speech.
Model Adaptation for ASR in low-resource Indian Languages
This is where a lot of adaptation and fine-tuning techniques can be applied to overcome the low-resource nature of the data by utilising well-resourced similar languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
A study on native American English speech recognition by Indian listeners with varying word familiarity level
We observe that the sentence, speaker difficulty ratings and the WERs increase from easy to hard categories of sentences.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Estimating articulatory movements in speech production with transformer networks
Additionally, on the AAI task, we obtain 1. 5%, 3% and 3. 1% relative gain in CC on the same setups compared to the state-of-the-art baseline.
Attention and Encoder-Decoder based models for transforming articulatory movements at different speaking rates
As the range of articulatory motions is correlated with speaking rate, we also analyze amplitude of the transformed articulatory movements at different rates compared to their original counterparts, to examine how well the proposed AstNet predicts the extent of articulatory movements in N2F and N2S.
A comparative study of estimating articulatory movements from phoneme sequences and acoustic features
While an attention network is used for estimating articulatory movement in the case of R2, BLSTM network is used for R1 and R3.
