From TOWER to SPIRE: Adding the Speech Modality to a Translation-Specialist LLM
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Abstract (arXiv)
We introduce Spire, a speech-augmented language model (LM) capable of both translating and transcribing speech input from English into 10 other languages as well as translating text input in both language directions. Spire integrates the speech modality into an existing multilingual LM via speech discretization and continued pre-training using only 42.5K hours of speech. In particular, we adopt the pretraining framework of multilingual LMs and treat discretized speech input as an additional translation language. This approach not only equips the model with speech capabilities, but also preserves its strong text-based performance. We achieve this using significantly less data than existing speech LMs, demonstrating that discretized speech input integration as an additional language is feasible during LM adaptation. We make our code and models available to the community.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 55 of its 74 references that are in the map. First posted on arXiv 13 Mar 2025.
Builds on
55 of 74 references.
References · 55
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38 more
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50 most cited of 55 All 55 (JSON)
Built on by
Citing papers per year: 2025: 4; 2026: 4.
8 papers.
- 2025NAVER LABS Europe Submission to the Instruction-following Trackcited by 5
- 2026SpeechMapper: Speech-to-text Embedding Projector for LLMscited by 4
- 2026Multimodal In-context Learning for ASR of Low-resource Languagescited by 2
- 2025Listening or Reading? Evaluating Speech Awareness in Chain-of-Thought Speech-to-Text Translationcited by 1
- 2026Why We Need Speech to Evaluate Speech Translationcited by 1
- 2025Instituto de Telecomunicacc~oes at IWSLT 2025: Aligning Small-Scale Speech and Language Models for Speech-to-Text Learningcited by 0
- 2025OmniFusion: Simultaneous Multilingual Multimodal Translations via Modular Fusioncited by 0
- 2026Two-Point Local Optimality in k-Means via Boundary-Point Screeningcited by 0
- 2026Two-Point Local Optimality in k-Means via Boundary-Point Screening5 Oct 2026
- 2026Why We Need Speech to Evaluate Speech Translation27 May 2026
- 2026SpeechMapper: Speech-to-text Embedding Projector for LLMs28 Jan 2026
- 2026Multimodal In-context Learning for ASR of Low-resource Languages9 Jan 2026
- 2025OmniFusion: Simultaneous Multilingual Multimodal Translations via Modular Fusion28 Nov 2025
- 2025Listening or Reading? Evaluating Speech Awareness in Chain-of-Thought Speech-to-Text Translation3 Oct 2025
- 2025Instituto de Telecomunicacc~oes at IWSLT 2025: Aligning Small-Scale Speech and Language Models for Speech-to-Text Learning20 Jun 2025
- 2025NAVER LABS Europe Submission to the Instruction-following Track2 Jun 2025