Categories: FAANG

Towards Real-World Streaming Speech Translation for Code-Switched Speech

This paper was accepted at the EMNLP Workshop on Computational Approaches to Linguistic Code-Switching (CALCS).
Code-switching (CS), i.e. mixing different languages in a single sentence, is a common phenomenon in communication and can be challenging in many Natural Language Processing (NLP) settings. Previous studies on CS speech have shown promising results for end-to-end speech translation (ST), but have been limited to offline scenarios and to translation to one of the languages present in the source (monolingual transcription).
In this paper, we focus on two essential yet unexplored areas…
AI Generated Robotic Content

Recent Posts

Update: Distilled v1.1 is live

We've pushed an LTX-2.3 update today. The Distilled model has been retrained (now v1.1) with…

19 hours ago

How to Implement Tool Calling with Gemma 4 and Python

The open-weights model ecosystem shifted recently with the release of the

19 hours ago

Structured Outputs vs. Function Calling: Which Should Your Agent Use?

Language models (LMs), at their core, are text-in and text-out systems.

19 hours ago

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts

This paper was accepted at the Workshop on Navigating and Addressing Data Problems for Foundation…

19 hours ago

How to build effective reward functions with AWS Lambda for Amazon Nova model customization

Building effective reward functions can help you customize Amazon Nova models to your specific needs,…

19 hours ago

How to find the sweet spot between cost and performance

At Google Cloud, we often see customers asking themselves: "How can we manage our generative…

19 hours ago