VoxCeleb Enrichment for Age and Gender Recognition
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Abstract (arXiv)
VoxCeleb datasets are widely used in speaker recognition studies. Our work serves two purposes. First, we provide speaker age labels and (an alternative) annotation of speaker gender. Second, we demonstrate the use of this metadata by constructing age and gender recognition models with different features and classifiers. We query different celebrity databases and apply consensus rules to derive age and gender labels. We also compare the original VoxCeleb gender labels with our labels to identify records that might be mislabeled in the original VoxCeleb data. On modeling side, we design a comprehensive study of multiple features and models for recognizing gender and age. Our best system, using i-vector features, achieved an F1-score of 0.9829 for gender recognition task using logistic regression, and the lowest mean absolute error (MAE) in age regression, 9.443 years, is obtained with ridge regression. This indicates challenge in age estimation from in-the-wild style speech data.
Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Builds on 10 of its 28 references that are in the map. First posted on arXiv 28 Sep 2021.
Builds on
10 of 28 references.
References · 10
- 2018VoxCeleb2: Deep Speaker Recognitioncited by 875
- 2017VoxCeleb: a large-scale speaker identification datasetcited by 732
- 2015Deep Speech 2: End-to-End Speech Recognition in English and Mandarincited by 451
- 2015MUSAN: A Music, Speech, and Noise Corpuscited by 425
- 2020Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatarscited by 118
- 2020Towards Learning a Universal Non-Semantic Representation of Speechcited by 84
- 2020End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractorscited by 71
- 2019Probing the Information Encoded in X-vectorscited by 18
- 2020AutoSpeech: Neural Architecture Search for Speaker Recognitioncited by 17
- 2019I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiencescited by 1
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Citing papers per year: 2022: 2; 2023: 4; 2024: 1; 2025: 7; 2026: 6.
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- 2023Joint Audio and Speech Understandingcited by 100
- 2023SpeechPrompt v2: Prompt Tuning for Speech Classification Taskscited by 32
- 2025AudioMarathon: A Comprehensive Benchmark for Long-Context Audio Understanding and Efficiency in Audio LLMscited by 22
- 2022Bias in Automated Speaker Recognitioncited by 20
- 2025WavReward: Spoken Dialogue Models With Generalist Reward Evaluatorscited by 15
- 2023UniverSLU: Universal Spoken Language Understanding for Diverse Tasks with Natural Language Instructionscited by 9
- 2026Do Audio LLMs Listen or Read? Analyzing and Mitigating Paralinguistic Failures with VoxParadoxcited by 7
- 2026WavBench: Benchmarking Reasoning, Colloquialism, and Paralinguistics for End-to-End Spoken Dialogue Modelscited by 6
- 2025Demographic Attributes Prediction from Speech Using WavLM Embeddingscited by 4
- 2025PAL: Probing Audio Encoders via LLMs -- Audio Information Transfer into LLMscited by 3
- 2025Enhancing Dialogue Annotation with Speaker Characteristics Leveraging a Frozen LLMcited by 3
- 2022Effects of language mismatch in automatic forensic voice comparison using deep learning embeddingscited by 1
8 more
- 2025Where Do Backdoors Live? A Component-Level Analysis of Backdoor Propagation in Speech Language Modelscited by 1
- 2026Cross-Language Speaker Attribute Prediction Using MIL and RLcited by 1
- 2026Speaker Verification with Speech-Aware LLMs: Evaluation and Augmentationcited by 1
- 2026Greater accessibility can amplify discrimination in generative AIcited by 1
- 2023Leveraging Speaker Embeddings with Adversarial Multi-task Learning for Age Group Classificationcited by 0
- 2024Disentangling Age and Identity with a Mutual Information Minimization Approach for Cross-Age Speaker Verificationcited by 0
- 2025VANPY: Voice Analysis Frameworkcited by 0
- 2026Voice Privacy from an Attribute-based Perspectivecited by 0
- 2026Do Audio LLMs Listen or Read? Analyzing and Mitigating Paralinguistic Failures with VoxParadox26 May 2026
- 2026Greater accessibility can amplify discrimination in generative AI23 Mar 2026
- 2026Voice Privacy from an Attribute-based Perspective19 Mar 2026
- 2026Speaker Verification with Speech-Aware LLMs: Evaluation and Augmentation11 Mar 2026
- 2026WavBench: Benchmarking Reasoning, Colloquialism, and Paralinguistics for End-to-End Spoken Dialogue Models12 Feb 2026
- 2026Cross-Language Speaker Attribute Prediction Using MIL and RL6 Jan 2026
- 2025AudioMarathon: A Comprehensive Benchmark for Long-Context Audio Understanding and Efficiency in Audio LLMs8 Oct 2025
- 2025Where Do Backdoors Live? A Component-Level Analysis of Backdoor Propagation in Speech Language Models1 Oct 2025
- 2025Enhancing Dialogue Annotation with Speaker Characteristics Leveraging a Frozen LLM6 Aug 2025
- 2025PAL: Probing Audio Encoders via LLMs -- Audio Information Transfer into LLMs12 Jun 2025
- 2025WavReward: Spoken Dialogue Models With Generalist Reward Evaluators14 May 2025
- 2025VANPY: Voice Analysis Framework17 Feb 2025
8 more
- 2025Demographic Attributes Prediction from Speech Using WavLM Embeddings17 Feb 2025
- 2024Disentangling Age and Identity with a Mutual Information Minimization Approach for Cross-Age Speaker Verification24 Sep 2024
- 2023UniverSLU: Universal Spoken Language Understanding for Diverse Tasks with Natural Language Instructions4 Oct 2023
- 2023Joint Audio and Speech Understanding25 Sep 2023
- 2023SpeechPrompt v2: Prompt Tuning for Speech Classification Tasks1 Mar 2023
- 2023Leveraging Speaker Embeddings with Adversarial Multi-task Learning for Age Group Classification22 Jan 2023
- 2022Effects of language mismatch in automatic forensic voice comparison using deep learning embeddings26 Sep 2022
- 2022Bias in Automated Speaker Recognition24 Jan 2022
- 2023Joint Audio and Speech Understandingcited by 100
- 2023SpeechPrompt v2: Prompt Tuning for Speech Classification Taskscited by 32
- 2022Bias in Automated Speaker Recognitioncited by 20
- 2023UniverSLU: Universal Spoken Language Understanding for Diverse Tasks with Natural Language Instructionscited by 9
- 2026Do Audio LLMs Listen or Read? Analyzing and Mitigating Paralinguistic Failures with VoxParadoxcited by 7
- 2025Demographic Attributes Prediction from Speech Using WavLM Embeddingscited by 4
- 2025PAL: Probing Audio Encoders via LLMs -- Audio Information Transfer into LLMscited by 3
- 2025Enhancing Dialogue Annotation with Speaker Characteristics Leveraging a Frozen LLMcited by 3
- 2022Effects of language mismatch in automatic forensic voice comparison using deep learning embeddingscited by 1
- 2026Cross-Language Speaker Attribute Prediction Using MIL and RLcited by 1
- 2026Speaker Verification with Speech-Aware LLMs: Evaluation and Augmentationcited by 1
- 2026Greater accessibility can amplify discrimination in generative AIcited by 1
12 most cited of 16 All 16 (JSON)
- 2026Do Audio LLMs Listen or Read? Analyzing and Mitigating Paralinguistic Failures with VoxParadox26 May 2026
- 2026Greater accessibility can amplify discrimination in generative AI23 Mar 2026
- 2026Voice Privacy from an Attribute-based Perspective19 Mar 2026
- 2026Speaker Verification with Speech-Aware LLMs: Evaluation and Augmentation11 Mar 2026
- 2026Cross-Language Speaker Attribute Prediction Using MIL and RL6 Jan 2026
- 2025Enhancing Dialogue Annotation with Speaker Characteristics Leveraging a Frozen LLM6 Aug 2025
- 2025PAL: Probing Audio Encoders via LLMs -- Audio Information Transfer into LLMs12 Jun 2025
- 2025VANPY: Voice Analysis Framework17 Feb 2025
- 2025Demographic Attributes Prediction from Speech Using WavLM Embeddings17 Feb 2025
- 2024Disentangling Age and Identity with a Mutual Information Minimization Approach for Cross-Age Speaker Verification24 Sep 2024
- 2023UniverSLU: Universal Spoken Language Understanding for Diverse Tasks with Natural Language Instructions4 Oct 2023
- 2023Joint Audio and Speech Understanding25 Sep 2023
12 newest of 16 All 16 (JSON)