SOTAVerified

Text to Speech

import gTTS import os def text_to_speech_kurdish(text, output_file="output.mp3"): # گۆڕینی نووسین بۆ دەنگ بە زمانی کوردی (هەڵبژاردنی زمانی "ku" بۆ کوردی) tts = gTTS(text=text, lang='ku', slow=False) tts.save(output_file) os.system(f"start {output_file}") # کردنەوەی فایلە دەنگییەکە (لە Windows) # نموونە: text_to_speech_kurdish("سڵاو، ئەمە دەنگی منە بە زمانی کوردی.")

Papers

Showing 131140 of 1419 papers

TitleStatusHype
JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to SpeechCode1
KazEmoTTS: A Dataset for Kazakh Emotional Text-to-Speech SynthesisCode1
EmoSpeech: Guiding FastSpeech2 Towards Emotional Text to SpeechCode1
EMNS /Imz/ Corpus: An emotive single-speaker dataset for narrative storytelling in games, television and graphic novelsCode1
A Character-level Span-based Model for Mandarin Prosodic Structure PredictionCode1
End-to-end Lyrics Alignment for Polyphonic Music Using an Audio-to-Character Recognition ModelCode1
Laugh Now Cry Later: Controlling Time-Varying Emotional States of Flow-Matching-Based Zero-Shot Text-to-SpeechCode1
EfficientSpeech: An On-Device Text to Speech ModelCode1
InstructTTSEval: Benchmarking Complex Natural-Language Instruction Following in Text-to-Speech SystemsCode1
Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided AttentionCode1
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