Distributional Metrics for Evaluating Spoken Conversational Systems
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Abstract (arXiv)
Evaluating conversational systems is a difficult and unresolved problem. We introduce the Conversational Distribution Score (CDS), which compares distributions of conversational behaviour using human conversations as a reference. CDS describes speech rate, syllabic rhythm, and turn interaction through eight interpretable features plus a separate two-feature semantic baseline. We compare conversations with two reference scales: one based on conversational success within human dialogue and another contrasting human and synthetic dialogue. Using listener judgments from out-of-domain goal--oriented dialogues, we examine system ranking, preferences between conversations, and ranking stability. Composite CDS recovers five of six listener system comparisons while individual features show strong correlation with listener preferences between conversations. We examine how many minutes and conversations are required before rankings stabilize. These findings support distributional comparisons as a complement to specific interactional metrics to evaluate conversations and conversational models while showing their interpretable value.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 20 of its 34 references that are in the map. First posted on arXiv 21 Sep 2026.
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References · 20
- 2023Neural Codec Language Models are Zero-Shot Text to Speech Synthesizerscited by 752
- 2024Moshi: a speech-text foundation model for real-time dialoguecited by 568
- 2023Voicebox: Text-Guided Multilingual Universal Speech Generation at Scalecited by 379
- 2021A Survey on Neural Speech Synthesiscited by 184
- 2022NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Qualitycited by 152
- 2022Generative Spoken Dialogue Language Modelingcited by 126
- 2025Full-Duplex-Bench: A Benchmark to Evaluate Full-duplex Spoken Dialogue Models on Turn-taking Capabilitiescited by 100
- 2020Universal Phone Recognition with a Multilingual Allophone Systemcited by 81
- 2026PersonaPlex: Voice and Role Control for Full Duplex Conversational Speech Modelscited by 63
- 2025Full-Duplex-Bench v1.5: Evaluating Overlap Handling for Full-Duplex Speech Modelscited by 54
- 2019Evaluating Coherence in Dialogue Systems using Entailmentcited by 53
- 2025Full-Duplex-Bench-v2: A Multi-Turn Evaluation Framework for Duplex Dialogue Systems with an Automated Examinercited by 41
8 more
- 2025MTR-DuplexBench: Towards a Comprehensive Evaluation of Multi-Round Conversations for Full-Duplex Speech Language Modelscited by 22
- 2024Sylber: Syllabic Embedding Representation of Speech from Raw Audiocited by 19
- 2024TTSDS -- Text-to-Speech Distribution Scorecited by 14
- 2025TTSDS2: Resources and Benchmark for Evaluating Human-Quality Text to Speech Systemscited by 8
- 2026M3-DuplexBench: A Multi-Turn, Multilingual, Multidomain Benchmark for Full-Duplex Spoken Dialogue Modelscited by 3
- 2026Acoustic and Facial Markers of Perceived Conversational Success in Spontaneous Speechcited by 2
- 2026Reference-Based Prosody and Rhythm Evaluation for Spoken Dialogue Systemscited by 2
- 2026SPEARBench: A Benchmark for Naturalness Evaluation in Streaming Speech-to-Speech Language Modelscited by 1
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