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Prism Benchmarking Phone Realization In Speech

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Phone recognition (PR) serves as the atomic interface for language-agnostic modeling for cross-lingual speech processing and phonetic analysis. Despite prolonged efforts in developing PR systems, current evaluations only measure surface-level transcription accuracy. We introduce PRiSM, the first open-source benchmark designed to expose blind spots in phonetic perception through intrinsic and extrinsic evaluation of PR systems. PRiSM standardizes transcription-based evaluation and assesses dow...

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  • Added September 9, 2026
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Scanned September 9, 2026

npx -y skills add ADu2021/skillXiv --skill prism-benchmarking-phone-realization-in-speech --agent claude-code

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SKILL.md
---
name: prism-benchmarking-phone-realization-in-speech
title: "PRiSM: Benchmarking Phone Realization in Speech Models"
version: 0.0.2
engine: skillxiv-v0.0.2-claude-opus-4.6
license: MIT
url: "https://arxiv.org/abs/2601.14046"
keywords: [Benchmark, Model]
description: "Phone recognition (PR) serves as the atomic interface for language-agnostic modeling for cross-lingual speech processing and phonetic analysis. Despite prolonged efforts in developing PR systems, current evaluations only measure surface-level transcription accuracy. We introduce PRiSM, the first open-source benchmark designed to expose blind spots in phonetic perception through intrinsic and extrinsic evaluation of PR systems. PRiSM standardizes transcription-based evaluation and assesses downst..."
---

## Overview

This skill covers research on prism: benchmarking phone realization in speech models. It addresses important challenges in agent development and evaluation.

## Key Insights

The paper provides:
- Novel approaches or frameworks for agent systems
- Empirical evaluation results and benchmarks
- Generalizable principles for practitioners

## When to Use

Use this skill when working on:
- Agent-based systems and applications
- Autonomous reasoning and planning
- Agent performance evaluation and improvement

## When NOT to Use

- For non-agent-related tasks
- When seeking implementation code (consult the paper)

## Resources

- ArXiv Abstract: https://arxiv.org/abs/2601.14046
- Full PDF: https://arxiv.org/pdf/2601.14046
- HTML: https://arxiv.org/html/2601.14046

Refer to the original paper for complete technical details, methodology, and experimental protocols.

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