23 citations · 23 across the 4 of their papers we have counts for
7 papers · 1 filter
Take the Hint: Improving Arabic Diacritization with Partially-Diacritized Text
Parnia Bahar, Mattia Di Gangi, Nick Rossenbach +1
Automatic Arabic diacritization is useful in many applications, ranging from reading support for language learners to accurate pronunciation predictor for downstream tasks like spe…
Tight Integrated End-to-End Training for Cascaded Speech Translation
Parnia Bahar, Tobias Bieschke, Ralf Schlüter +1
A cascaded speech translation model relies on discrete and non-differentiable transcription, which provides a supervision signal from the source side and helps the transformation b…
Two-Way Neural Machine Translation: A Proof of Concept for Bidirectional Translation Modeling using a Two-Dimensional Grid
Parnia Bahar, Christopher Brix, Hermann Ney
Neural translation models have proven to be effective in capturing sufficient information from a source sentence and generating a high-quality target sentence. However, it is not e…
On using 2D sequence-to-sequence models for speech recognition
Parnia Bahar, Albert Zeyer, Ralf Schlüter +1
Attention-based sequence-to-sequence models have shown promising results in automatic speech recognition. Using these architectures, one-dimensional input and output sequences are…
On Using SpecAugment for End-to-End Speech Translation
Parnia Bahar, Albert Zeyer, Ralf Schlüter +1
This work investigates a simple data augmentation technique, SpecAugment, for end-to-end speech translation. SpecAugment is a low-cost implementation method applied directly to the…
A Comparative Study on End-to-end Speech to Text Translation
Parnia Bahar, Tobias Bieschke, Hermann Ney
Recent advances in deep learning show that end-to-end speech to text translation model is a promising approach to direct the speech translation field. In this work, we provide an o…