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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

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Showing 1151–1175 of 1419 papers

TitleStatusHype
RW-Resnet: A Novel Speech Anti-Spoofing Model Using Raw Waveform—0
S2ST-Omni: An Efficient and Scalable Multilingual Speech-to-Speech Translation Framework via Seamless Speech-Text Alignment and Streaming Speech Generation—0
Sadeed: Advancing Arabic Diacritization Through Small Language Model—0
SALF-MOS: Speaker Agnostic Latent Features Downsampled for MOS Prediction—0
SALMONN-omni: A Codec-free LLM for Full-duplex Speech Understanding and Generation—0
SALTTS: Leveraging Self-Supervised Speech Representations for improved Text-to-Speech Synthesis—0
Sample Efficient Adaptive Text-to-Speech—0
SANE-TTS: Stable And Natural End-to-End Multilingual Text-to-Speech—0
SANIP: Shopping Assistant and Navigation for the visually impaired—0
SATTS: Speaker Attractor Text to Speech, Learning to Speak by Learning to Separate—0
Scalable Multilingual Frontend for TTS—0
Scale This, Not That: Investigating Key Dataset Attributes for Efficient Speech Enhancement Scaling—0
Schrodinger Bridges Beat Diffusion Models on Text-to-Speech Synthesis—0
SeamlessEdit: Background Noise Aware Zero-Shot Speech Editing with in-Context Enhancement—0
Seeing Voices: Generating A-Roll Video from Audio with Mirage—0
SegINR: Segment-wise Implicit Neural Representation for Sequence Alignment in Neural Text-to-Speech—0
Segmentation-Variant Codebooks for Preservation of Paralinguistic and Prosodic Information—0
SelectTTS: Synthesizing Anyone's Voice via Discrete Unit-Based Frame Selection—0
Self-Attention Linguistic-Acoustic Decoder—0
Semi-supervised Sequence-to-sequence ASR using Unpaired Speech and Text—0
Semi-Supervised Generative Modeling for Controllable Speech Synthesis—0
Semi-Supervised Learning Based on Reference Model for Low-resource TTS—0
Semi-supervised Learning for Multi-speaker Text-to-speech Synthesis Using Discrete Speech Representation—0
Semi-Supervised Training for Improving Data Efficiency in End-to-End Speech Synthesis—0
Semi-supervised transfer learning for language expansion of end-to-end speech recognition models to low-resource languages—0
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