Human-Guided Reasoning with Large Language Models for Vietnamese Speech Emotion Recognition

Human-Guided Reasoning with Large Language Models for Vietnamese Speech Emotion Recognition | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/human-guided-reasoning-with-large-language-models-for-vietnamese-speech-emotion-recognition

stale

Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-04-03
Score updated: 2026-04-03
Score fresh until: 2026-05-03
References: 0
Source count: 0
Coverage: 33%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Canonical ID human-guided-reasoning-with-large-language-models-for-vietnamese-speech-emotion-recognition | Route /signal-canvas/human-guided-reasoning-with-large-language-models-for-vietnamese-speech-emotion-recognition

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/human-guided-reasoning-with-large-language-models-for-vietnamese-speech-emotion-recognition

MCP example

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source_context

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Evidence Receipt

Route status: building

Claims: 8

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Human-Guided Reasoning with Large Language Models for Vietnamese Speech Emotion Recognition

PDF: https://arxiv.org/pdf/2604.01711v1

Source count: Pending verification

Coverage: 33%

Last proof check: 2026-04-03T20:50:40.820Z

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Watch and verify: Human-Guided Reasoning with Large Language Models for Vietnamese Speech Emotion Recognition

/buildability/human-guided-reasoning-with-large-language-models-for-vietnamese-speech-emotion-recognition

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Subject: Human-Guided Reasoning with Large Language Models for Vietnamese Speech Emotion Recognition

Verdict

Watch

Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

Preparing verified analysis

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No public code linked for this paper yet.

Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
The proposed method achieves strong performance, reaching up to 86.59% accuracy
Implicationpartial
Explicitly stated in abstract with specific numeric result
Verificationpartial
partial
Evidencepartial
A confidence-based routing mechanism is introduced to distinguish between easy and ambiguous samples
Implicationpartial
Directly stated in abstract as a core component of the method
Verificationpartial
partial
Evidencepartial
Macro F1 around 0.85-0.86, demonstrating its effectiveness
Implicationpartial
Explicitly stated in abstract with specific numeric range
Verificationpartial
partial
Evidencepartial
Vietnamese Speech Emotion Recognition (SER) remains challenging due to ambiguous acoustic patterns and the lack of reliable annotated data
Implicationpartial
Directly stated as problem motivation in abstract
Verificationpartial
partial
Evidencepartial
LLM-based reasoning, where acoustic feature-based models are used to provide auxiliary signals
Implicationpartial
Directly stated as core method component in abstract
Verificationpartial
partial
Evidencepartial
Experiments are conducted on a Vietnamese speech dataset of 2,764 samples across three emotion classes
Implicationpartial
Explicitly stated with specific dataset details
Verificationpartial
partial
Evidencepartial
with high inter-annotator agreement (Fleiss Kappa = 0.8574), ensuring reliable ground truth
Implicationpartial
Explicitly stated with specific statistical measure
Verificationpartial
partial
Evidencepartial
an iterative refinement strategy is employed to continuously improve system performance through error analysis and rule updates
Implicationpartial
Directly stated as part of the method description
Verificationpartial
partial

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Human-Guided Reasoning with Large Language Models for Vietnamese Speech Emotion Recognition

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