"Speech recognition technology and systems" matching MCP servers:

MCP server for intelligent circuit diagram recognition, enabling detection of components, text, topology, and netlist from circuit images.

MCP server integrating VolcEngine for automatic speech recognition (ASR) and text-to-speech (TTS), converting audio to text or text to audio files.

An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.

A Goose MCP extension providing voice interaction with modern audio visualization, allowing users to communicate with Goose through speech rather than text.

Enables AI agents to manage system updates, application installations, and remote host orchestration through MCP tools.

An MCP server that provides local image recognition on macOS, including OCR, image classification, comprehensive image analysis, and screenshot recognition, all via Apple's Vision framework without any network requests.

Provides image recognition capabilities using Anthropic Claude Vision and OpenAI GPT-4 Vision APIs, supporting multiple image formats and offering optional text extraction via Tesseract OCR.

Retrieves, parses, and analyzes speeches and testimonies from Federal Reserve officers, enabling searches by speaker, topic, and keyword with automatic RSS feed discovery and intelligent relevance scoring.

Provides read-only access to public African language speech corpora, with tools to list, search, cite, and plan de-duplicated training sets while enforcing licence and citation provenance.

Enables voice-coaching hosts to analyze speech across delivery, language, fluency, pronunciation, and emotional state, then synthesize structured coaching feedback that can be spoken aloud.

Local MCP server for neural text-to-speech using Kokoro ONNX engine on CPU, supporting SSML tags, multiple voice profiles, and zero-GPU operation for low-latency speech synthesis.

Enables image analysis and recognition through multiple LLM vision models (Gemini, GPT-4o, Qwen-VL, Doubao) by accepting image URLs or Base64 data and returning text descriptions or answers to questions about the images.

Text-to-speech MCP server that enables AI assistants to read text aloud on the user's computer using Windows SAPI, with no API key or cloud service required.

Enables search and retrieval of speech turns from Korea's National Assembly records using Korean or English natural-language queries, with citation-ready context and tools for exploring committees and meetings.

Runs a local, file-based toolkit of 100 systems engineering skills that lets an AI assistant clean and map requirements, review specifications against ECSS, derive sub-requirements, check interfaces and budgets, and build verification and compliance matrices. It works on documents in a user-chosen local folder without sending customer data to a remote service or requiring an account or API key.

An MCP server that provides speech-to-text transcription and speaker diarization using OpenAI Whisper and pyannote.audio.

Enables high-performance audio transcription using Faster Whisper with CUDA acceleration, supporting single and batch audio file processing with multiple output formats (VTT, SRT, JSON).

Serves plain-text notes that an Obsidian user has explicitly published for AI over streamable HTTP, with full-text and embedding-based search. MCP clients can read and search those notes and queue suggested edits that the user's own client applies only if the AI rules allow it.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.