116 citations · 199 across the 5 of their papers we have counts for
5 papers
Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
Microsoft, :, Abdelrahman Abouelenin +73
We introduce Phi-4-Mini and Phi-4-Multimodal, compact yet highly capable language and multimodal models. Phi-4-Mini is a 3.8-billion-parameter language model trained on high-qualit…
Have best of both worlds: two-pass hybrid and E2E cascading framework for speech recognition
Guoli Ye, Vadim Mazalov, Jinyu Li +1
Hybrid and end-to-end (E2E) systems have their individual advantages, with different error patterns in the speech recognition results. By jointly modeling audio and text, the E2E m…
Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability
Jinyu Li, Rui Zhao, Zhong Meng +8
Because of its streaming nature, recurrent neural network transducer (RNN-T) is a very promising end-to-end (E2E) model that may replace the popular hybrid model for automatic spee…
Speaker-Invariant Training via Adversarial Learning
Zhong Meng, Jinyu Li, Zhuo Chen +5
We propose a novel adversarial multi-task learning scheme, aiming at actively curtailing the inter-talker feature variability while maximizing its senone discriminability so as to…
Unsupervised Adaptation with Domain Separation Networks for Robust Speech Recognition
Zhong Meng, Zhuo Chen, Vadim Mazalov +2
Unsupervised domain adaptation of speech signal aims at adapting a well-trained source-domain acoustic model to the unlabeled data from target domain. This can be achieved by adver…