Search Results for "dtmf decoder python"
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Showing 6 open source projects for "dtmf decoder python"
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CSM (Conversational Speech Model)
A Conversational Speech Generation Model
The CSM (Conversational Speech Model) is a speech generation model developed by Sesame AI that creates RVQ audio codes from text and audio inputs. It uses a Llama backbone and a smaller audio decoder to produce audio codes for realistic speech synthesis. The model has been fine-tuned for interactive voice demos and is hosted on platforms like Hugging Face for testing. CSM offers a flexible setup and is compatible with CUDA-enabled GPUs for efficient execution. -
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LaMDA-pytorch
Open-source pre-training implementation of Google's LaMDA in PyTorch
Open-source pre-training implementation of Google's LaMDA research paper in PyTorch. The totally not sentient AI. This repository will cover the 2B parameter implementation of the pre-training architecture as that is likely what most can afford to train. You can review Google's latest blog post from 2022 which details LaMDA here. You can also view their previous blog post from 2021 on the model. -
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stable-video-diffusion-img2vid-xt
Generates high-quality short videos from a single still image input
... frame-wise decoder and a fine-tuned f8-decoder to enhance coherence across frames. Despite its high quality, output videos are short (under 4 seconds) and not always fully photorealistic. Faces, text, and realistic motion may be inconsistently rendered, and the model cannot generate legible writing. It is suited for creative video generation, research, and educational applications under a community license, with image-level watermarking enabled by default. -
4
Kokoro-82M
Lightweight, fast, and high-quality open TTS model with 82M params
Kokoro-82M is an open-weight, lightweight text-to-speech (TTS) model featuring 82 million parameters, developed to deliver high-quality voice synthesis with exceptional efficiency. Despite its compact size, Kokoro rivals the output quality of much larger models while remaining significantly faster and cheaper to run. Built on StyleTTS2 and ISTFTNet architectures, it uses a decoder-only setup without diffusion, enabling rapid audio generation with low computational overhead. Kokoro supports... -
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5
whisper-large-v3
High-accuracy multilingual speech recognition and translation model
Whisper-large-v3 is OpenAI’s most advanced multilingual automatic speech recognition (ASR) and speech translation model, featuring 1.54 billion parameters and trained on 5 million hours of labeled and pseudo-labeled audio. Built on a Transformer-based encoder-decoder architecture, it supports 99 languages and delivers significant improvements in transcription accuracy, robustness to noise, and handling of diverse accents. Compared to previous versions, v3 introduces a 128 Mel bin spectrogram... -
6
chronos-t5-small
Time series forecasting model using T5 architecture with 46M params
chronos-t5-small is part of Amazon’s Chronos family of time series forecasting models built on transformer-based language model architectures. It repurposes the T5 encoder-decoder design for time series data by transforming time series into discrete tokens via scaling and quantization. With 46 million parameters and a reduced vocabulary of 4096 tokens, this small variant balances performance with efficiency. Trained on both real-world and synthetic time series datasets, it supports...
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