6 papers
PashtoTTS-Bench: automated screening for low-resource non-Latin-script text-to-speech
Hanif Rahman
Text-to-speech (TTS) evaluation for low-resource non-Latin-script languages can fail when it relies on a single ASR round-trip word error rate (WER). A system may produce no audio,…
Script collapse in multilingual ASR: A reference-free metric and 100-pair benchmark
Hanif Rahman
Word error rate (WER) is the dominant metric for automatic speech recognition, yet it cannot detect a systematic failure mode: models that produce fluent output in the wrong writin…
Fine-tuning Whisper for Pashto ASR: strategies and scale
Hanif Rahman
Pashto is absent from Whisper's pre-training corpus despite being one of CommonVoice's largest language collections, leaving off-the-shelf models unusable: all Whisper sizes output…
Benchmarking Multilingual Speech Models on Pashto: Zero-Shot ASR, Script Failure, and Cross-Domain Evaluation
Hanif Rahman
Pashto is spoken by approximately 60--80 million people but has no published benchmarks for multilingual automatic speech recognition (ASR) on any shared public test set. This pape…
Pashto Common Voice: Building the First Open Speech Corpus for a 60-Million-Speaker Low-Resource Language
Hanif Rahman, Shafeeq ur Rehman
We present the Pashto Common Voice corpus -- the first large-scale, openly licensed speech resource for Pashto, a language with over 60 million native speakers largely absent from…
PashtoCorp: A 1.25-Billion-Word Corpus, Evaluation Suite, and Reproducible Pipeline for Low-Resource Language Development
Hanif Rahman
We present PashtoCorp, a 1.25-billion-word corpus for Pashto, a language spoken by 60 million people that remains severely underrepresented in NLP. The corpus is assembled from 39…