gigaam-v3-ctc-gguf is an open-source Russian ASR model using CTC decoding, distributed in GGUF format for use with local inference tools. It supports quantized variants for efficient offline transcription. Below are 7 voice, tts & speech apps with similar functionality to Gigaam V3 Ctc, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
gigaam-v3-e2e-ctc-gguf is an open-source Russian automatic speech recognition model using CTC decoding, distributed in GGUF format for use with local inference tools. It supports quantized variants for efficient offline transcription.
gigaam-v3-rnnt-gguf is an open-source automatic speech recognition model for Russian, distributed in GGUF format for use with transcribe.cpp and similar tools. It uses RNN-T decoding and supports quantized variants for efficient offline transcription.
gigaam-v3-e2e-rnnt-gguf is an open-source Russian ASR model using RNN-T decoding, distributed in GGUF format for local inference. It is suitable for developers and researchers needing efficient offline speech-to-text solutions.
parakeet-ctc-0.6b-gguf is an open-source automatic speech recognition model using CTC decoding. It allows developers and researchers to transcribe audio to text efficiently, supporting both local and API-based inference. Suitable for speech AI and transcription projects.
parakeet-ctc-1.1b-gguf is an open-source speech-to-text model based on the Parakeet CTC architecture, designed for offline and API-based transcription. It supports English audio input and is suitable for developers and researchers building ASR solutions.
OmniVoice-GGUF is an open-source text-to-speech AI model distributed via Hugging Face. It allows developers and researchers to perform local voice synthesis and voice cloning for various applications. The model is suitable for experimentation, prototyping, and integration into speech-enabled systems.
Voxtral-Mini-4B-Realtime-2602-gguf is an open-source automatic speech recognition (ASR) model supporting 13 languages. It enables developers to transcribe audio to text locally using the GGUF format and integrates with tools like transcribe.cpp. Ideal for building multilingual ASR solutions.
