Create README.md

README.md

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+---
+metrics:
+- wer
+- cer
+library_name: transformers
+pipeline_tag: automatic-speech-recognition
+tags:
+- Cretan
+- Greek dialect
+---
+
+# Cretan XLS-R model
+
+Cretan is a variety of Modern Greek predominantly used by speakers who reside on the island of Crete or 
+belong to the Cretan diaspora. This includes communities of Cretan origin that were relocated to the 
+village of Hamidieh in Syria and to Western Asia Minor, following the population exchange between 
+Greece and Turkey in 1923. The historical and geographical factors that have shaped the development 
+and preservation of the dialect include the long-term isolation of Crete from the mainland, and the 
+successive domination of the island by foreign powers, such as the Arabs, the Venetians, and the Turks, 
+over a period of seven centuries. Cretan has been divided based on its phonological, phonetic, 
+morphological, and lexical characteristics into two major dialect groups: the western and the eastern. 
+The boundary between these groups coincides with the administrative division of the island into the 
+prefectures of Rethymno and Heraklion. Kontosopoulos (2008) argues that the eastern dialect group is more 
+homogeneous than the western one, which shows more variation across all levels of linguistic analysis. 
+Contrary to other Modern Greek Dialects, Cretan does not face the threat of extinction, as it remains 
+the sole means of communication for a large number of speakers in various parts of the island.
+
+This is the first automatic speech recognition (ASR) model for Cretan. 
+To train the model, we fine-tuned a Greek XLS-R model ([jonatasgrosman/wav2vec2-large-xlsr-53-greek](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-greek)) on 11h of recorded Pomak speech.
+
+## Resources
+
+For the compilation of the Cretan corpus, we gathered 32 tapes containing material from  
+radio broadcasts in digital format, with permission from the Audiovisual Department of the 
+Vikelaia Municipal Library of Heraklion, Crete. These broadcasts were recorded and 
+aired by Radio Mires, in the Messara region of Heraklion, during the period 1998-2001, 
+totaling 958 minutes and 47 seconds. These recordings primarily consist of narratives 
+by one speaker, Ioannis Anagnostakis, who is responsible for their composition. In terms 
+of textual genre, the linguistic content of the broadcasts consists of folklore 
+narratives expressed in the local linguistic variety. Out of the total volume of material 
+collected, we utilized nine tapes. Criteria for material selection included, on the one hand, 
+maximizing digital clarity of speech and, on the other hand, ensuring representative sampling 
+across the entire three-year period of radio recordings. To obtain an initial transcription, 
+we employed the Large-v2 model, which was the largest Whisper model at the time. Subsequently, 
+the transcripts were manually corrected in collaboration with the local community. 
+The transcription system that was used was based on the Greek alphabet and orthography
+and it was annotated in Praat.
+
+To prepare the dataset, the texts were normalized (see [greek_dialects_asr/](https://gitlab.com/ilsp-spmd-all/speech/greek_dialects_asr/) for scripts), 
+and all audio files were converted into a 16 kHz mono format.
+
+We split the Praat annotations into audio-transcription segments, which resulted in a dataset of a total duration of 1h 21m 12s.
+Note that the removal of music, long pauses, and non-transcribed segments leads to a reduction of the total audio duration 
+(compared to the initial 2h recordings of the 9 tapes).
+
+## Metrics
+
+We evaluated the model on the test set split, which consists of 10% of the dataset recordings.
+
+|Model|WER|CER|
+|---|---|---|
+|pre-trained|104.83%|91.73%|
+|fine-tuned|28.27%|7.88%|
+
+## Training hyperparameters
+
+We fine-tuned the baseline model (`wav2vec2-large-xlsr-53-greek`) on an NVIDIA GeForce RTX 3090, using the following hyperparameters:
+
+| arg                           | value |
+|-------------------------------|-------|
+| `per_device_train_batch_size` | 8     |
+| `gradient_accumulation_steps` | 2     |
+| `num_train_epochs`            | 35    |
+| `learning_rate`               | 3e-4  |
+| `warmup_steps`                | 500   |
+
+## Citation
+
+To cite this work or read more about the training pipeline, see:
+
+S. Vakirtzian, C. Tsoukala, S. Bompolas, K. Mouzou, V. Stamou, G. Paraskevopoulos, A. Dimakis, S. Markantonatou, A. Ralli, A. Anastasopoulos, Speech Recognition for Greek Dialects: A Challenging Benchmark, Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH), 2024.