--- title: "Cascaded Modular or End-to-End? : An Investigation on" description: "This workshop paper compares two design choices for Tamil, Telugu and Kannada: a cascaded modular pipeline… 7.03 BLEU. 8 references." authors: ["Bhavana Nali", "Abhik Jana"] year: 2026 venue: "Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages" source: "https://aclanthology.org/2026.dravidianlangtech-1.3/" doi: "10.18653/v1/2026.dravidianlangtech-1.3" licence: "CC BY 4.0 (ACL Anthology)" licence_url: "https://creativecommons.org/licenses/by/4.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/nali-2026-cascaded-modular-or-end-end/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/nali-2026-cascaded-modular-or-end-end/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/25/) / Cascaded Modular or End-to-End? : An Investigation on Speech-to-Speech Translation Task for Dravidian Languages # Cascaded Modular or End-to-End? : An Investigation on Speech-to-Speech Translation Task for Dravidian Languages **Authors:** Bhavana Nali and [Abhik Jana](https://md.research.elamur.ai/free/en/authors/abhik-jana/) · **Year:** 2026 · **Venue:** [Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages](https://md.research.elamur.ai/free/en/venues/dravidianlangtech/) ([Workshop on Speech, Vision, and Language Technologies for Dravidian Languages 2026](https://md.research.elamur.ai/free/en/venues/dravidianlangtech/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/) **Links:** [Publisher's page](https://aclanthology.org/2026.dravidianlangtech-1.3/) · [PDF](https://aclanthology.org/2026.dravidianlangtech-1.3.pdf) · [DOI 10.18653/v1/2026.dravidianlangtech-1.3](https://doi.org/10.18653/v1/2026.dravidianlangtech-1.3) · [OpenAlex](https://openalex.org/W7166824292) **Citations:** 0 citations (OpenAlex, 2026-10-14) ## Summary Speech-to-speech translation for Dravidian languages has seen little systematic study, mainly because parallel speech data are scarce. This workshop paper compares two design choices for Tamil, Telugu and Kannada: a cascaded modular pipeline and a single End-to-End model. The cascade chains a recognizer with IndicTrans2 for text translation and Indic Parler-TTS for synthesis. The recognizer is Whisper Large-v3 for English input and IndicConformer for Dravidian input. SeamlessM4T-v2 serves as the End-to-End counterpart. Both systems are tested zero-shot and after LoRA adaptation on FLEURS and the Mann-ki-Baat portion of BhasaAnuvaad, in English→Dravidian and Dravidian→Dravidian directions. Mann-ki-Baat has no direct Dravidian pairs, so the authors build them automatically with LaBSE similarity and Hungarian matching. Evaluation uses BLEU, chrF++ and COMET, plus WER/CER from re-transcribing the generated audio. The cascade wins in most configurations, though some gaps are under one BLEU point and no significance tests were run. LoRA tuning brings clear gains, especially between Dravidian languages. The work is a first joint benchmark of both paradigms for these languages, and the code is public. ## Key points - BLEU ranges: the cascade scores 3.17–18.96 zero-shot and 5.08–19.18 fine-tuned. SeamlessM4T-v2 scores 3.02–15.72 and 4.11–16.84. The best result is EN→Telugu on FLEURS (19.18 vs 16.84 after tuning). - LoRA setup: rank 16, scaling 32, dropout 0.1, with under 1% of parameters trainable. Training ran 4,000 steps with batch size 8 and learning rate 1e-4. Indic Parler-TTS stayed frozen. - Data: about 3,000 FLEURS utterances per language. Mann-ki-Baat yields roughly 15,284 aligned pairs (similarity threshold 0.6), split 80/10/10. - Dravidian→Dravidian gains: Ta→Te rises from 8.13 to 10.12 and Ta→Kn from 6.73 to 8.74. Error propagation is visible for EN→Tamil on FLEURS: MT BLEU is 17.42 with gold transcripts but 14.81 with ASR input. English ASR WER falls from 0.124 to 0.089. - Caveats: - Using IndicConformer for back-ASR may slightly favour the cascade. - There was no human evaluation of naturalness. - The automatic alignments were not validated. - Fine-tuning did not always help: cascaded EN→Kannada on Mann-ki-Baat dropped from 8.70 to 7.03 BLEU. *Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.* ## Institutions Also on the byline: [Indian Institute of Technology Bhubaneswar](https://ror.org/04gx72j20). 📚 Shelves (5): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 16,667 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 16,194 works · [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 16,039 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 15,891 works · [🔊 Signal Processing](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/) · 452 works 🧭 Topics (1): [🎙️ Speech & spoken language](https://md.research.elamur.ai/free/en/topics/speech/) · 480 works ## Cite Cite as: Bhavana Nali and Abhik Jana. 2026. Cascaded Modular or End-to-End? : An Investigation on Speech-to-Speech Translation Task for Dravidian Languages. Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages. The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{nali2026cascaded, title = {{Cascaded Modular or End-to-End? : An Investigation on Speech-to-Speech Translation Task for Dravidian Languages}}, author = {Bhavana Nali and Abhik Jana}, booktitle = {Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages}, year = {2026}, doi = {10.18653/v1/2026.dravidianlangtech-1.3}, url = {https://doi.org/10.18653/v1/2026.dravidianlangtech-1.3} } ``` - [← previous CasbAI at AraSentEval 2026: Robust Dialectal Arabic Sentiment Classification via Multi-Seed Ensembling and Data Augmentation.](https://md.research.elamur.ai/free/en/papers/abdelaziz-2026-casbai-arasenteval-2026-robust-dialectal/) - [next → CATS: An Annotation Scheme of Causality and Temporal Structure](https://md.research.elamur.ai/free/en/papers/yu-2026-cats-annotation-scheme-causality-temporal/) - [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/25/) ## References 8 references, 5 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. 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Towards building large scale datasets and state-of-the-art automatic speech translation systems for 14 indian languages. In Proce… [find](https://scholar.google.com/scholar?q=Ashwin+Sankar%2C+Sparsh+Jain%2C+Nikhil+Narasimhan%2C+Devilal+Choudhary%2C+Dhairya+Suman%2C+Mohammed+Safi+Ur+Rahman+Khan%2C+Anoop+Kunchukuttan%2C+Mitesh+M%2E+Khapra%2C+and+Raj+Dabre%2E+2025a%2E+Towards+building+large+scale+) 6. Jay Gala, Pranjal A Chitale, A K Raghavan, Varun Gumma, Sumanth Doddapaneni, Aswanth Kumar M, Janki Atul Nawale, Anupama Sujatha, Ratish Puduppully, Vivek Raghavan, Pratyush Kumar, Mitesh M Khapra, Raj Dabre, and Anoop Kunchukuttan. 2023. [Indictrans2: Towards high-quality and accessible machine tran…](https://md.research.elamur.ai/free/en/papers/gala-2023-indictrans2-towards-high-quality-accessible/) 7. Ashwin Sankar, Yoach Lacombe, Sherry Thomas, Praveen Srinivasa Varadhan, Sanchit Gandhi, and Anmol Gulati, James Qin, Chung-Cheng Chiu, Niki Mitesh M. Khapra. 2025b. 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