Bhiksha Raj
Professor
Studies speech and audio processing, machine learning for audio and privacy-preserving speech technologies.
Bhiksha Raj's lab at CMU works on speech recognition & spoken language and music, audio & sound. 90 papers since 2023, 68 at top venues, mostly ICASSP and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 23/ year
- at T1 venues
- 76%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 5 papers2026 · T1 2 · collecting
- 27 papers2025 · T1 19
- 32 papers2024 · T1 24
- 26 papers2023 · T1 23
T1 venuesOtherVenues: ICASSP, NeurIPS, ICLR, Interspeech, CVPR
Research focuspaper titles that use each topic's words
- Speech recognition & spoken language31 papers
- speech15 papers
- Music, audio & sound10 papers
- audio10 papers
- technologies0 papers
Paper list
From DBLP.
20265 papers
- Comput. Speech Lang.Exploring features for membership inference in ASR model auditing (opens in a new tab)
- ICANNFrom Scalar Rewards to Dense Feedback: Dense Reward Shaping for U-MLLM Post-training (opens in a new tab)
- ACM Trans. Intell. Syst. Technol.Introduction to the Special Issue on Evaluations of Large Language Models Part 2 (opens in a new tab)
- ICLR (T1)VideoJudge: Bootstrapping Enables Scalable Supervision of MLLM-as-a-Judge for Video Understanding (opens in a new tab)
- CVPR (T1)φ-DPO: Fairness Direct Preference Optimization Approach to Continual Learning in Large Multimodal Models (opens in a new tab)
202527 papers
- ICLR (T1)ADIFF: Explaining audio difference using natural language (opens in a new tab)
- AAAI (T1)Audio Entailment: Assessing Deductive Reasoning for Audio Understanding (opens in a new tab)
- IJCV (T1)Autoregressive Temporal Modeling for Advanced Tracking-by-Diffusion (opens in a new tab)
- Findings of EMNLPCAARMA: Class Augmentation with Adversarial Mixup Regularization (opens in a new tab)
- ASRUCoLMbo: Speaker Language Model for Descriptive Profiling (opens in a new tab)
- NeurIPS (T1)Directed-Tokens: A Robust Multi-Modality Alignment Approach to Large Language-Vision Models (opens in a new tab)
- CVPR (T1)FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene Understanding (opens in a new tab)
- ICLR (T1)ImageFolder: Autoregressive Image Generation with Folded Tokens (opens in a new tab)
- TPAMI (T1)Impact of Noisy Supervision in Foundation Model Learning (opens in a new tab)
- ACM Trans. Intell. Syst. Technol.Introduction to the Special Issue on Evaluations of Large Language Models: Part 1 (opens in a new tab)
- Findings of ACLLost in Transcription, Found in Distribution Shift: Demystifying Hallucination in Speech Foundation Models (opens in a new tab)
- ICASSP WorkshopMACE: Leveraging Audio for Evaluating Audio Captioning Systems (opens in a new tab)
202432 papers
- Comput. Speech Lang.A closer look at reinforcement learning-based automatic speech recognition (opens in a new tab)
- ICML (T1)A General Framework for Learning from Weak Supervision (opens in a new tab)
- ICASSP (T1)AugSumm: Towards Generalizable Speech Summarization Using Synthetic Labels from Large Language Models (opens in a new tab)
- NAACL (T1)AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition (opens in a new tab)
- ICML (T1)Completing Visual Objects via Bridging Generation and Segmentation (opens in a new tab)
- Findings of ACLContinual Contrastive Spoken Language Understanding (opens in a new tab)
- Interspeech (T1)DeWinder: Single-Channel Wind Noise Reduction using Ultrasound Sensing (opens in a new tab)
- Interspeech (T1)Domain Adaptation for Contrastive Audio-Language Models (opens in a new tab)
- ICASSP (T1)Dynamic-Superb: Towards a Dynamic, Collaborative, and Comprehensive Instruction-Tuning Benchmark For Speech (opens in a new tab)
- NeurIPS (T1)EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding (opens in a new tab)
- SLTESPnet-Codec: Comprehensive Training and Evaluation of Neural Codecs For Audio, Music, and Speech (opens in a new tab)
- ICPRFashion Image Retrieval with Occlusion (opens in a new tab)
202326 papers
- ICASSP (T1)An Approach to Ontological Learning from Weak Labels (opens in a new tab)
- IJCV (T1)AOE-Net: Entities Interactions Modeling with Adaptive Attention Mechanism for Temporal Action Proposals Generation (opens in a new tab)
- Interspeech (T1)BASS: Block-wise Adaptation for Speech Summarization (opens in a new tab)
- ASRUEspnet-Summ: Introducing a Novel Large Dataset, Toolkit, and a Cross-Corpora Evaluation of Speech Summarization Systems (opens in a new tab)
- NeurIPS (T1)Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments (opens in a new tab)
- CVPR (T1)FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding (opens in a new tab)
- ICLR (T1)FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning (opens in a new tab)
- ICML (T1)How Many Perturbations Break This Model? Evaluating Robustness Beyond Adversarial Accuracy (opens in a new tab)
- ICASSP (T1)Paaploss: A Phonetic-Aligned Acoustic Parameter Loss for Speech Enhancement (opens in a new tab)
- NeurIPS (T1)PaintSeg: Painting Pixels for Training-free Segmentation (opens in a new tab)
- ICCV (T1)Pairwise Similarity Learning is SimPLE (opens in a new tab)
- AAAI (T1)Panoramic Video Salient Object Detection with Ambisonic Audio Guidance (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to CMUFall 2027
CMU SCS Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL / IELTS / Duolingo (F-1/J-1 non-native speakers)
- Fee
- USD 100 (USD 80 by early deadline)
Confirmed on the program page.
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Data
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