Search Results for "tamil speech recognition"
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68 projects for "tamil speech recognition" with 1 filter applied:
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Cloudbrink Personal SASE serviceCloudbrink’s Personal SASE is a high-performance connectivity and security service that delivers a lightning-fast, in-office experience to the modern hybrid workforce anywhere. Combining high-performance ZTNA with Automated Moving Target Defense (AMTD), and Personal SD-WAN all connections are ultra-secure.
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Free Website Monitoring Service | UptimeRobotWith the Free Plan, you can monitor up to 50 URLs, check for a website's content (using the keyword monitor), ping your server or monitor your ports in 5-minute intervals. You can create a status page to showcase your uptime. SMS or Call alerts can be bought anytime.
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Hugging Face - Speech To Speech
Open speech-to-speech models and pipelines by Hugging Face toolkit AI
This project from Hugging Face focuses on enabling direct speech-to-speech processing using modern machine learning models. It provides tools and reference implementations that allow audio input to be transformed into audio output without requiring an intermediate text representation. Hugging Face - Speech To Speech builds on recent advances in speech modeling, combining components such as speech recognition, translation, and synthesis into unified pipelines. ... -
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Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
OpenAI Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. ... -
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SenseVoice
Multilingual speech recognition and audio understanding model
SenseVoice is a speech foundation model designed to perform multiple voice understanding tasks from audio input. It provides capabilities such as automatic speech recognition, spoken language identification, speech emotion recognition, and audio event detection within a single system. SenseVoice is trained on more than 400,000 hours of speech data and supports over 50 languages for multilingual recognition tasks. -
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Kimi-Audio
Audio foundation model excelling in audio understanding
Kimi-Audio is an ambitious open-source audio foundation model designed to unify a wide array of audio processing tasks — from speech recognition and audio understanding to generative conversation and sound event classification — within a single cohesive architecture. Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. ... -
ERP Software To Simplify Your ManufacturingGlobal Shop Solutions AI-integrated ERP software provides the applications needed to deliver a quality part on time, every time from quote to cash and everything in between, including shop management, scheduling, inventory, accounting, quality control, CRM and 25 more.
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StreamSpeech
StreamSpeech is a seamless model for offline speech recognition
StreamSpeech is an “all-in-one” speech model designed to perform offline and simultaneous speech recognition, speech translation, and speech synthesis within a single unified architecture. Developed as part of an ACL 2024 paper, it targets streaming and low-latency scenarios where intermediate results and final translations or synthetic speech must be produced continuously as audio is being received. -
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WhisperJAV
Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD
WhisperJAV is an open-source speech transcription pipeline designed specifically for generating subtitles for Japanese adult video content. The project addresses challenges that standard speech recognition models face when transcribing this type of audio, which often includes low signal-to-noise ratios and large numbers of non-verbal vocalizations. Traditional automatic speech recognition systems can misinterpret these sounds as words, leading to inaccurate transcripts. ... -
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Ultravox
Fast multimodal LLM for real-time voice interaction and AI apps
Ultravox is an open source multimodal large language model designed specifically for real-time voice-based interactions. It is built to process both text and spoken audio directly, eliminating the need for a separate speech recognition stage and enabling more seamless conversational experiences. Ultravox works by combining text prompts with encoded audio inputs, allowing it to understand spoken language alongside written instructions in a unified pipeline. Internally, it leverages pretrained language models and speech encoders, with a multimodal adapter that integrates both modalities for inference and training. ... -
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BrowserAI
Run local LLMs like llama, deepseek, kokoro etc. inside your browser
...The platform provides a developer-friendly SDK with pre-configured popular models, and it allows for seamless switching between MLC and Transformer engines. Additionally, it supports features such as speech recognition, text-to-speech, structured output generation, and Web Worker support for non-blocking UI performance. -
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Pipecat
Framework for building real-time voice and multimodal AI agents
Pipecat is an open source Python framework designed for building real-time voice and multimodal conversational AI agents. It provides developers with tools to orchestrate complex pipelines that combine speech recognition, language models, audio processing, and speech synthesis into a cohesive conversational system. Pipecat focuses on low-latency interactions so voice conversations with AI feel natural and responsive during live use. Pipecat allows applications to integrate multiple AI services and transports, enabling flexible deployment across different environments and communication channels. ... -
We help you deliver Virtual and Hybrid Events using our Award Winning end-to-end Event Management PlatformEventsAIR have been anticipating and responding to the ever-changing event industry needs for over 30 years, providing innovative solutions that empower event organizers to create successful events around the globe.
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ESPnet
End-to-end speech processing toolkit
ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. -
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VideoChat
Real-time voice interactive digital human
VideoChat is a real-time voice-interactive “digital human” system that combines automatic speech recognition, large language models, text-to-speech, and talking-head generation into a single conversational pipeline. It supports both pure end-to-end voice solutions based on multimodal large language models (GLM-4-Voice feeding directly into talking-head generation) and a more traditional cascaded pipeline using ASR → LLM → TTS → talking head. -
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Streamer-Sales
LLM Large Model of Selling Anchor
...By analyzing product characteristics and marketing information, the model can produce engaging explanations that emphasize benefits, features, and emotional appeal to encourage viewers to make purchasing decisions. The system integrates multiple AI technologies including retrieval-augmented generation to incorporate product knowledge, speech synthesis to convert generated scripts into voice output, and digital human generation to create virtual hosts. It also supports automatic speech recognition and agent-based tools that can retrieve additional information such as logistics or product details during live sessions. -
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Open-LLM-VTuber
Open source AI VTuber platform with voice chat and Live2D avatars
Open-LLM-VTuber is an open source platform designed to create AI-powered VTuber characters that can interact with users through voice and animated avatars. It enables hands-free conversations with large language models by combining speech recognition, language processing, and text-to-speech synthesis into a single system. Users can speak directly to the AI character, and the system can respond with a generated voice while animating a Live2D avatar to simulate a talking virtual personality. Open-LLM-VTuber is modular, allowing developers to swap or configure different language models, speech recognition engines, and voice synthesis systems depending on their needs. ... -
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Qwen3-ASR
Qwen3-ASR is an open-source series of ASR models
Qwen3-ASR is an automatic speech recognition system in the QwenLM family, developed to convert spoken language into text with strong accuracy and real-time performance. As a specialized ASR variant of the broader Qwen language model ecosystem, it focuses on capturing reliable transcriptions from audio sources such as recordings, live streams, or conversational inputs while supporting low latency use cases. -
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Fun Audio Chat
Large Audio Language Model built for natural interactions
Fun Audio Chat is an interactive voice-first conversational AI platform designed to let users engage in natural spoken dialogue with large language models in real time, turning speech into context-aware responses while maintaining a smooth back-and-forth experience. It combines speech recognition, audio processing, and AI generation so users can speak simply and receive spoken replies, enabling applications such as virtual assistants, voice bots, and hands-free chat interfaces. The system supports dynamic audio input and output, meaning it can handle different voices, tones, and conversational contexts without forcing users into typed interactions. ... -
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VideoCaptioner
AI-powered tool for generating, optimizing, and translating subtitles
VideoCaptioner is an open source AI-powered subtitle processing tool designed to simplify the workflow of creating subtitles for videos. It integrates speech recognition, language processing, and translation technologies to automatically generate and refine subtitles from video or audio sources. VideoCaptioner uses speech-to-text engines such as Whisper variants to transcribe spoken content and convert it into subtitle text with accurate timestamps. After transcription, large language models are used to intelligently restructure subtitles into natural sentences, correct wording, and improve readability for viewers. ... -
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RunAnywhere
Production ready toolkit to run AI locally
...It also includes integrated pipelines that combine speech-to-text, large language models, and text-to-speech into a complete conversational system. -
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Lingvo
Framework for building neural networks
...It has been used to implement state of the art architectures such as recurrent neural networks, Transformer models, variational autoencoder hybrids, and multi task systems. Lingvo includes reference models and configurations for domains like machine translation, automatic speech recognition, language modeling, image understanding, and 3D object detection. Centralized hyperparameter configuration files allow researchers to share exact experiment setups so others can retrain and compare results reliably. -
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comfyui-mixlab-nodes
Workflow and speech recognition app
comfyui-mixlab-nodes is a large collection of custom nodes for ComfyUI that turns workflows into interactive apps and adds real-time multimedia, LLM, and TTS capabilities. It introduces a “Workflow-to-APP” concept, where a ComfyUI graph can be transformed into a Web App through an AppInfo node, complete with categories, batch prompts, and editable configurations. The project also brings Real-time Design features like screen capture and floating video nodes, enabling creative pipelines that... -
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Textream
Textream is a free macOS teleprompter app for streamers, interviewers
Textream is an open-source, free macOS teleprompter application designed for streamers, podcasters, presenters, and interviewers who want a smooth, distraction-free way to stay on script. It runs natively on macOS and leverages on-device speech recognition to highlight each word in real time as you speak, keeping your focus where it belongs — on delivery rather than memorization. The interface supports multiple modes of use, such as classic constant-scroll auto-scrolling, voice-activated scrolling that pauses when you’re silent, and direct word tracking that syncs the displayed script to your spoken pace. ... -
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BasedHardware
Open source AI wearable platform for recording and summarizing speech
...Omi includes firmware for wearable hardware, a Flutter-based mobile companion application, backend services built with Python and FastAPI, and various SDKs for developers. These components work together to process audio, perform speech recognition, and integrate AI features such as summaries and automated actions. Developers can extend the platform by building plugins, integrations, and custom applications using provided SDKs and APIs. The repository also supports experimental hardware implementations. -
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ElatoAI
Realtime AI Voice Agents with SoTA Multimodal AI models on Arduino ESP
ElatoAI is a real-time AI voice agent platform built around IoT hardware (ESP32) that enables continuous speech-to-speech conversations using state-of-the-art multimodal voice models with minimal latency and global performance via edge computing. The system integrates voice synthesis and recognition by connecting an ESP32 device through secure WebSockets to edge server functions written in Deno, allowing users to speak naturally with AI agents hosted through cloud APIs including OpenAI’s Realtime API, Gemini’s Live API, xAI’s Grok Voice Agent API, and others. ... -
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Whisper-WebUI
A Web UI for easy subtitle using whisper model
Whisper WebUI is an open-source browser-based interface that simplifies the use of Whisper speech recognition models by providing an intuitive graphical environment for transcription, translation, and subtitle generation. Built with Gradio, it allows users to upload audio or video files, process them locally, and generate accurate text outputs without relying on command-line tools. The platform integrates optimized implementations such as faster-whisper, significantly improving transcription speed and reducing memory usage compared to standard models. ... -
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Seamless Communication
Foundational Models for State-of-the-Art Speech and Text Translation
Seamless Communication is a research project focused on building more integrated, low-latency multimodal communication between humans and AI agents. The motivation is to move beyond “text in, text out” and enable direct, live, multi-turn exchange involving language, gesture, gaze, vision, and modality switching without user friction. The system architecture includes a real-time multimodal signal pipeline for audio, video, and sensor data, a dialog manager that can decide when to act (speak,... -
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LLPlayer
The media player for language learning, with dual subtitles
LLPlayer is an open-source media player designed specifically for language learning through video content. Unlike traditional media players, the application focuses on advanced subtitle-related features that help learners understand and interact with foreign language media more effectively. The player supports dual subtitles so users can simultaneously view text in both the original language and their native language while watching videos. It can also automatically generate subtitles in real...
