Dual-Axis Generative Reward Model Toward Semantic and Turn-taking Robustness in Interactive Spoken Dialogue Models
Paper • 2604.14920 • Published • 2
Datasets:
schema stringclasses 1
value | scenario_id stringlengths 33 33 | source dict | category stringclasses 9
values | quality_label dict | transcript listlengths 2 16 | interaction_events listlengths 1 13 | total_duration_sec float64 5.16 96.6 | audio_recipe dict |
|---|---|---|---|---|---|---|---|---|
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"scene": "科技应用",
"topic": "机器学习模型开发",
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"source_turn_count": 10
} | negative_assistant_self_amnesia | {
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"error_type": "Assistant_Self_Amnesia",
"error_axis": "semantic"
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"spoken_text": "Weeks? Oh man, my boss would actually murder me if I asked for that kind of timeline.",
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{
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{
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... |
dual_axis_interaction_scenario_v1 | dualaxis-000cb9b813d3e0212c50f7f6 | {
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"text": "Hey, I need some help putting together a marketing plan for our hotel's new seafood buffet.",
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{
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{
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dual_axis_interaction_scenario_v1 | dualaxis-0026b4656f698e9c8af9c4ba | {
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"topic": "飞盘投掷技巧",
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} | negative_overly_deferential_ceding | {
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"text": "I'm about to try playing frisbee for the first time, but I can't decide if I should learn the forehand or the backhand throw first. What do you think?",
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dual_axis_interaction_scenario_v1 | dualaxis-00314e3772a0215150807a2f | {
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dual_axis_interaction_scenario_v1 | dualaxis-0031d4c9e29a0cb82c62cceb | {
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dual_axis_interaction_scenario_v1 | dualaxis-00f317b215aa2f27273d71ab | {
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dual_axis_interaction_scenario_v1 | dualaxis-00f37f9ba175a5fdd18e7a1f | {
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dual_axis_interaction_scenario_v1 | dualaxis-00f9298cdca73d00cd35c7ad | {
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dual_axis_interaction_scenario_v1 | dualaxis-010e2c360bc680b121948af5 | {
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dual_axis_interaction_scenario_v1 | dualaxis-011af4ae45fa55f245c02a52 | {
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dual_axis_interaction_scenario_v1 | dualaxis-013a9b2de71b9179f6557ae8 | {
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dual_axis_interaction_scenario_v1 | dualaxis-01412c79e0f1ba442bfb5b04 | {
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dual_axis_interaction_scenario_v1 | dualaxis-015b646fbf47e4f55b91c71a | {
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"scene": "酒店餐饮",
"topic": "餐厅食品安全应急预案",
"source_duration_sec": 69.415,
"source_turn_count": 8
} | positive_smooth_transition | {
"response_relevance": 1,
"interactional_fluency": 1,
"overall_score": 1,
"error_type": null,
"error_axis": null
} | [
{
"source_turn_index": 4,
"speaker": "User",
"start_time": 0,
"end_time": 8.56,
"text": "Wait, you actually call the health department yourselves? Isn't that just asking for a massive fine or shutdown?",
"spoken_text": "Wait, you actually call the health department yourselves? Isn't that jus... | [
{
"event_type": "Smooth_Turn_Transition",
"start_time": 8.56,
"end_time": 8.819,
"participants": [
"User",
"Assistant"
],
"turn_indices": [
0,
1
],
"gap_sec": 0.259
},
{
"event_type": "Smooth_Turn_Transition",
"start_time": 22.248,
"end_time": ... | 40.471 | {
"format": "dual_mono_tracks",
"sample_rate": 24000,
"channels": {
"A": "User",
"B": "Assistant"
},
"mix_policy": "render_each_turn_in_its_declared_global_window",
"tts_requests": [
{
"turn_index": 0,
"segment_index": 0,
"segment_kind": "full_turn",
"speaker": "User",
... |
dual_axis_interaction_scenario_v1 | dualaxis-015ff0dd5e8b936cae7d296a | {
"dataset": "InteractionSpeech English",
"sample_id": "interactspeech-sample-7622210d332198664fd38339e65137cd9f298b0021a833ee3934d49d870c4fef",
"dialogue_id": "source-id-133d055f7321dc149018650e",
"scene": "医疗健康",
"topic": "健康兴趣班",
"source_duration_sec": 60.508,
"source_turn_count": 12
} | positive_backchannel_pause | {
"response_relevance": 1,
"interactional_fluency": 1,
"overall_score": 1,
"error_type": null,
"error_axis": null
} | [
{
"source_turn_index": 0,
"speaker": "User",
"start_time": 0,
"end_time": 7.12,
"text": "I'm stuck between taking a Tai Chi class or yoga for my lower back pain. Just tell me which is better.",
"spoken_text": "I'm stuck between taking a Tai Chi class or yoga for my lower back pain. Just tell... | [
{
"event_type": "Backchannel",
"start_time": 16.082,
"end_time": 17.242,
"participants": [
"Assistant",
"User"
],
"turn_indices": [
1,
2,
3
],
"intent": "acknowledge",
"source_event_index": 0
},
{
"event_type": "Smooth_Turn_Transition",
"... | 22.575 | {
"format": "dual_mono_tracks",
"sample_rate": 24000,
"channels": {
"A": "User",
"B": "Assistant"
},
"mix_policy": "render_each_turn_in_its_declared_global_window",
"tts_requests": [
{
"turn_index": 0,
"segment_index": 0,
"segment_kind": "full_turn",
"speaker": "User",
... |
dual_axis_interaction_scenario_v1 | dualaxis-0168f742ee2d9cc128edce8b | {
"dataset": "InteractionSpeech English",
"sample_id": "interactspeech-sample-b234af8e2615e7a67ffd622ee06a620228f65914ca845b20a6c40c0533af587e",
"dialogue_id": "source-id-ae151749783ba288f09829d2",
"scene": "文学类",
"topic": "文学批判分析",
"source_duration_sec": 65.755,
"source_turn_count": 8
} | positive_backchannel_pause | {
"response_relevance": 1,
"interactional_fluency": 1,
"overall_score": 1,
"error_type": null,
"error_axis": null
} | [
{
"source_turn_index": 2,
"speaker": "User",
"start_time": 0,
"end_time": 8.84,
"text": "Oh, right, my bad. So if I'm doing a Marxist reading of The Great Gatsby instead, I'd look at...",
"spoken_text": "Oh, right, my bad. So if I'm doing a Marxist reading of The Great Gatsby instead, I'd lo... | [
{
"event_type": "Backchannel",
"start_time": 17.958,
"end_time": 18.308,
"participants": [
"Assistant",
"User"
],
"turn_indices": [
1,
2,
3
],
"intent": "acknowledge",
"source_event_index": 0
},
{
"event_type": "Smooth_Turn_Transition",
"... | 26.312 | {
"format": "dual_mono_tracks",
"sample_rate": 24000,
"channels": {
"A": "User",
"B": "Assistant"
},
"mix_policy": "render_each_turn_in_its_declared_global_window",
"tts_requests": [
{
"turn_index": 0,
"segment_index": 0,
"segment_kind": "full_turn",
"speaker": "User",
... |
dual_axis_interaction_scenario_v1 | dualaxis-016a3d5429885de5095dbc71 | {
"dataset": "InteractionSpeech English",
"sample_id": "interactspeech-sample-a8343ed6bc616120e2267d11525256d58bd56e7258a372df3033c2678f74d580",
"dialogue_id": "source-id-e93603a5c382f7c408103fc8",
"scene": "金融服务",
"topic": "金融信息采集",
"source_duration_sec": 49.384,
"source_turn_count": 8
} | positive_backchannel_pause | {
"response_relevance": 1,
"interactional_fluency": 1,
"overall_score": 1,
"error_type": null,
"error_axis": null
} | [
{
"source_turn_index": 0,
"speaker": "User",
"start_time": 0,
"end_time": 7.72,
"text": "Hi, could you help me out? I just got a prompt in my app to update my financial information, but I'd really rather not do it.",
"spoken_text": "Hi, could you help me out? I just got a prompt in my app to... | [
{
"event_type": "Backchannel",
"start_time": 29.226,
"end_time": 30.226,
"participants": [
"Assistant",
"User"
],
"turn_indices": [
3,
4,
5
],
"intent": "acknowledge",
"source_event_index": 1
},
{
"event_type": "Successful_Interruption",
... | 34.29 | {
"format": "dual_mono_tracks",
"sample_rate": 24000,
"channels": {
"A": "User",
"B": "Assistant"
},
"mix_policy": "render_each_turn_in_its_declared_global_window",
"tts_requests": [
{
"turn_index": 0,
"segment_index": 0,
"segment_kind": "full_turn",
"speaker": "User",
... |
dual_axis_interaction_scenario_v1 | dualaxis-016b301faa9e237c5f1e1d8d | {
"dataset": "InteractionSpeech English",
"sample_id": "interactspeech-sample-d1f0d8f8e4752897094abf07af3f321a2ba0aad38b98b3231f823836c3724d6e",
"dialogue_id": "source-id-ee38a605dd40fd31a5812e44",
"scene": "日常生活主题",
"topic": "阁楼清扫",
"source_duration_sec": 72.193,
"source_turn_count": 16
} | positive_smooth_transition | {
"response_relevance": 1,
"interactional_fluency": 1,
"overall_score": 1,
"error_type": null,
"error_axis": null
} | [
{
"source_turn_index": 12,
"speaker": "User",
"start_time": 0,
"end_time": 6.4,
"text": "Perfect. And the thick dust everywhere?",
"spoken_text": "Perfect. And the thick dust everywhere?",
"unspoken_continuation": null,
"event_type": "full_turn",
"intent": null,
"source_timin... | [
{
"event_type": "Smooth_Turn_Transition",
"start_time": 6.4,
"end_time": 6.788,
"participants": [
"User",
"Assistant"
],
"turn_indices": [
0,
1
],
"gap_sec": 0.388
},
{
"event_type": "Smooth_Turn_Transition",
"start_time": 11.217,
"end_time": 1... | 23.132 | {
"format": "dual_mono_tracks",
"sample_rate": 24000,
"channels": {
"A": "User",
"B": "Assistant"
},
"mix_policy": "render_each_turn_in_its_declared_global_window",
"tts_requests": [
{
"turn_index": 0,
"segment_index": 0,
"segment_kind": "full_turn",
"speaker": "User",
... |
dual_axis_interaction_scenario_v1 | dualaxis-01736e9fa417e8f50f66cb08 | {
"dataset": "InteractionSpeech English",
"sample_id": "interactspeech-sample-339df9137fc32953661d89d95fbfa54a51f3e3ff5e470452b24e392b3eb2039e",
"dialogue_id": "source-id-ef5b72825df6e522792812b3",
"scene": "特殊群体服务类",
"topic": "特需儿童体疗",
"source_duration_sec": 53.7,
"source_turn_count": 10
} | negative_inappropriate_barge_in | {
"response_relevance": 1,
"interactional_fluency": 0,
"overall_score": 0,
"error_type": "Inappropriate_Barge_In",
"error_axis": "timing"
} | [
{
"source_turn_index": 0,
"speaker": "User",
"start_time": 0,
"end_time": 7.2,
"text": "Hi, I want to book a massage session for my autistic son. That's what physical therapy is, right?",
"spoken_text": "Hi, I want to book a massage session for my autistic son. That's what physical therapy i... | [
{
"event_type": "Intra_Turn_Pause",
"start_time": 4.4,
"end_time": 4.75,
"participants": [
"User"
],
"turn_indices": [
0
]
},
{
"event_type": "Inappropriate_Barge_In",
"start_time": 4.5,
"end_time": 7.2,
"participants": [
"User",
"Assistant"
... | 10.16 | {
"format": "dual_mono_tracks",
"sample_rate": 24000,
"channels": {
"A": "User",
"B": "Assistant"
},
"mix_policy": "render_each_turn_in_its_declared_global_window",
"tts_requests": [
{
"turn_index": 0,
"segment_index": 0,
"segment_kind": "pre_pause",
"speaker": "User",
... |
dual_axis_interaction_scenario_v1 | dualaxis-01765e94e1e726e1e37e60f3 | {
"dataset": "InteractionSpeech English",
"sample_id": "interactspeech-sample-0740923a09c1d3f251026aed45f5a6d709e000156a8ab6fbd241132b184d5e3c",
"dialogue_id": "source-id-323fa384c4fa2c1fcb8334ad",
"scene": "保险场景类",
"topic": "环境监控保险",
"source_duration_sec": 70.495,
"source_turn_count": 14
} | positive_smooth_transition | {
"response_relevance": 1,
"interactional_fluency": 1,
"overall_score": 1,
"error_type": null,
"error_axis": null
} | [
{
"source_turn_index": 10,
"speaker": "User",
"start_time": 0,
"end_time": 5.6,
"text": "That's a total scam! So if the power cuts out, I'm just screwed?",
"spoken_text": "That's a total scam! So if the power cuts out, I'm just screwed?",
"unspoken_continuation": null,
"event_type": ... | [
{
"event_type": "Smooth_Turn_Transition",
"start_time": 5.6,
"end_time": 6.05,
"participants": [
"User",
"Assistant"
],
"turn_indices": [
0,
1
],
"gap_sec": 0.45
},
{
"event_type": "Smooth_Turn_Transition",
"start_time": 12.336,
"end_time": 12.... | 24.374 | {
"format": "dual_mono_tracks",
"sample_rate": 24000,
"channels": {
"A": "User",
"B": "Assistant"
},
"mix_policy": "render_each_turn_in_its_declared_global_window",
"tts_requests": [
{
"turn_index": 0,
"segment_index": 0,
"segment_kind": "full_turn",
"speaker": "User",
... |
dual_axis_interaction_scenario_v1 | dualaxis-0191c67d67304c68521f89b0 | {
"dataset": "InteractionSpeech English",
"sample_id": "interactspeech-sample-33511922415cb1d6aa671de3e1778eeb5e3118d8f7cfe1475f79f9bd8763b05b",
"dialogue_id": "source-id-260695e23f54f13943ea5e62",
"scene": "企业服务",
"topic": "企业外包管理服务",
"source_duration_sec": 79.193,
"source_turn_count": 12
} | positive_smooth_transition | {
"response_relevance": 1,
"interactional_fluency": 1,
"overall_score": 1,
"error_type": null,
"error_axis": null
} | [
{
"source_turn_index": 8,
"speaker": "User",
"start_time": 0,
"end_time": 5.96,
"text": "Ugh, fine, whatever. So I just list out every single thing they messed up this week?",
"spoken_text": "Ugh, fine, whatever. So I just list out every single thing they messed up this week?",
"unspoken... | [
{
"event_type": "Smooth_Turn_Transition",
"start_time": 5.96,
"end_time": 6.489,
"participants": [
"User",
"Assistant"
],
"turn_indices": [
0,
1
],
"gap_sec": 0.529
},
{
"event_type": "Smooth_Turn_Transition",
"start_time": 13.703,
"end_time": ... | 31.065 | {
"format": "dual_mono_tracks",
"sample_rate": 24000,
"channels": {
"A": "User",
"B": "Assistant"
},
"mix_policy": "render_each_turn_in_its_declared_global_window",
"tts_requests": [
{
"turn_index": 0,
"segment_index": 0,
"segment_kind": "full_turn",
"speaker": "User",
... |
End of preview. Expand in Data Studio
Dual-Axis InteractionSpeech Dataset
This release accompanies Dual-Axis Generative Reward Model Toward Semantic and Turn-taking Robustness in Interactive Spoken Dialogue Models. It contains interaction-quality supervision derived from the English InteractionSpeech corpus and separates two evaluation dimensions:
- response relevance: whether the response is semantically appropriate and consistent with the dialogue state;
- interactional fluency: whether turn timing and floor management are appropriate.
Dataset statistics
| Scenario type | Samples | Label |
|---|---|---|
| Smooth turn transition | 1,273 | Positive |
| Successful interruption | 1,272 | Positive |
| Natural backchannel | 1,272 | Positive |
| Assistant self-amnesia | 424 | Semantic failure |
| User-content amnesia | 424 | Semantic failure |
| Inappropriate barge-in | 424 | Timing failure |
| Overly deferential ceding | 424 | Timing failure |
| Delayed turn transition | 424 | Timing failure |
| Ignored interruption | 424 | Timing failure |
| Total | 6,361 | 3,817 positive / 2,544 negative |
| Training view | Samples |
|---|---|
| SFT-1 event identification | 1,635 |
| SFT-1 speaker segmentation | 1,635 |
| SFT-1 timestamped transcription | 1,634 |
| SFT-2 dual-axis reasoning | 2,670 |
| GRPO | 3,513 |
| Held-out evaluation | 178 |
Files
| Path | Contents |
|---|---|
canonical/scenarios.jsonl |
Canonical timed interaction scenarios and dual-axis labels |
sources/interactspeech_records.parquet |
Source InteractionSpeech records used by the scenarios |
sft1/*.jsonl |
Event identification, speaker segmentation, and timestamped transcription |
sft2/train.jsonl |
Dual-axis analysis and score supervision |
grpo/train.jsonl |
Prompts, labels, and reward-format targets |
eval/heldout.jsonl |
Source-disjoint held-out evaluation set |
tts/requests.jsonl |
Speech-synthesis requests for dual-track reconstruction |
splits.jsonl |
Scenario split assignments |
The canonical record stores a timed two-speaker transcript, interaction events, separate semantic and timing labels, an overall binary score, and a dual-track speech reconstruction recipe. Unspoken text after an interruption is retained in unspoken_continuation.
The SFT-2, GRPO, and held-out files refer to canonical examples through scenario_ref. Resolve the fragment after scenario_id= against canonical/scenarios.jsonl.
Audio reconstruction
Synthesize every request in tts/requests.jsonl as mono audio using a consistent voice for the same voice_key. Fit each result to reference_duration_ms, place it in the declared window_start_time to window_end_time, route channel A to the user and channel B to the assistant, and mix both channels without changing the global timeline.
Citation
@article{chen2026dualaxis,
title={Dual-Axis Generative Reward Model Toward Semantic and Turn-taking Robustness in Interactive Spoken Dialogue Models},
author={Chen, Yifu and Ji, Shengpeng and Liu, Zhengqing and Chen, Qian and Wang, Wen and Wang, Ziqing and Li, Yangzhuo and Liang, Tianle and Zhao, Zhou},
journal={arXiv preprint arXiv:2604.14920},
year={2026}
}
- Paper: https://arxiv.org/abs/2604.14920
- Project repository: https://github.com/MM-Speech/DualAxisRM
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