SpeechPulse
Related Servers
Alternatives to SpeechPulse
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityBmaintenanceEnables agents to analyze speech prosody and vocal sentiment, including speech rate, pitch variance, and cognitive fatigue, to dynamically calibrate response pacing.7-
- FlicenseNot gradedqualityBmaintenanceEnables analysis of acoustic vocal emotion, prosodic valence, and customer frustration from audio inputs through a zero-dependency MCP server.7-
- FlicenseNot gradedqualityBmaintenanceEnables MCP-compliant agents to analyze speech prosody and vocal sentiment from audio-derived input, measuring speech rate, pitch variance, and user cognitive fatigue. Exposes these deterministic results over JSON-RPC so clients can dynamically calibrate their response pacing.7-
- AlicenseAqualityCmaintenanceProvides local audio analysis tools for LLMs, enabling transcription, conversation dynamics, prosody analysis, and visual inspection without API keys.8MIT
- FlicenseNot gradedqualityBmaintenanceEnables real-time voice agents to dynamically tailor speech pitch, cadence, and pause inflections through low-latency prosody, SSML, and emotion pacing modulation.7-
- FlicenseNot gradedqualityBmaintenanceEnables real-time voice agents to dynamically modulate speech pitch, cadence, and pause inflections via prosody, SSML, and emotion pacing for low-latency conversational audio.7-
TDQS
Scored across 5 tools
Tools have distinct focuses (emotion, urgency, sarcasm, health) but full_analysis overlaps by combining all three analyses, creating potential confusion for an agent choosing between individual and combined tools.
Most tools follow a verb_noun pattern (analyze_audio, assess_urgency, detect_sarcasm) but full_analysis and health_check deviate, mixing noun phrases and lacking consistent verb usage.
With 5 tools, the server covers core audio analysis tasks (emotion, urgency, sarcasm) plus a combined analysis and health check, which is well-scoped and reasonable for the domain.
The set covers emotion, urgency, and sarcasm detection, but lacks a dedicated transcription tool (ASR is optional via parameter) and other potential features like speaker identification, leaving moderate gaps.