Overview
This model is a state-of-the-art text-to-speech system designed for the Central Kurdish (ckb) language. This model converts written text into natural and intelligible spoken words, providing an essential tool for various applications such as accessibility, language learning, and content creation.
Datasets
- Dataset Name: PawanKrd/tts-ckb
- Description: This dataset comprises a diverse collection of Central Kurdish texts and corresponding audio recordings, meticulously curated to train and evaluate this model.
Model Performance
This model has been evaluated on the PawanKrd/tts-ckb dataset, achieving the following performance metrics:
Loss: 19.1
- Explanation: This metric measures the discrepancy between the predicted audio and the actual audio. A lower loss indicates better performance.
SER (Sentence Error Rate): 34.66%
- Explanation: This metric quantifies the percentage of sentences with errors in the generated speech. A lower SER indicates more accurate and reliable speech synthesis.
Applications
This model can be utilized in various scenarios, including but not limited to:
- Accessibility: Enhancing the accessibility of written content for individuals with visual impairments.
- Language Learning: Assisting learners in acquiring proper pronunciation and listening skills in Central Kurdish.
- Content Creation: Enabling the creation of audio content such as podcasts, audiobooks, and announcements in Central Kurdish.
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Inference Providers
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This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.