# Advanced Rich Transcription System for Estonian Speech

arXiv: https://arxiv.org/abs/1901.03601 · HTML: https://mlsanity.com/paper/1901.03601/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jan 2019.

## Built on by (most cited first, 1 of 1)

- [A Comparison of Methods for OOV-word Recognition on a New Public Dataset](https://mlsanity.com/paper/2107.08091/) (2021)

## Abstract (arXiv)

This paper describes the current TT"U speech transcription system for Estonian speech. The system is designed to handle semi-spontaneous speech, such as broadcast conversations, lecture recordings and interviews recorded in diverse acoustic conditions. The system is based on the Kaldi toolkit. Multi-condition training using background noise profiles extracted automatically from untranscribed data is used to improve the robustness of the system. Out-of-vocabulary words are recovered using a phoneme n-gram based decoding subgraph and a FST-based phoneme-to-grapheme model. The system achieves a word error rate of 8.1% on a test set of broadcast conversations. The system also performs punctuation recovery and speaker identification. Speaker identification models are trained using a recently proposed weakly supervised training method.