Update README.md

README.md

@@ -26,76 +26,4 @@ The core objectives include:
 - ensuring robustness across heterogeneous conditions (telephone bandwidth, online conferencing, real-world noise);
 - maintaining strong multilingual capabilities while specializing in French;
 - delivering reproducible and scientifically-rigorous evaluation frameworks;
-- enabling deployment on sovereign infrastructures with strict data governance constraints.
-
----
-
-## 2. Research Themes
-
-### **2.1 High-precision French ASR**
-Tailored to:
-
-- meetings and long-form speech  
-- lectures and institutional discourse  
-- spontaneous multi-speaker environments  
-- regional and international accents  
-
-### **2.2 Multilingual preservation**
-Although optimized for French, models are evaluated to maintain strong cross-lingual performance.
-
-### **2.3 Robustness, frugality, and domain adaptation**
-Research includes:
-
-- noise augmentation and channel variability  
-- 8 kHz telephony adaptation  
-- low-compute inference  
-- distillation for edge deployment  
-
-### **2.4 Benchmarking and dataset engineering**
-Gilbert designs domain-specific datasets and benchmark suites for evaluating ASR in conditions representative of operational environments.
-
----
-
-## 3. Current Model Family
-
-### **Gilbert-FR-Source (2025)**
-Baseline model fine-tuned on curated high-quality French corpora; foundation for all domain-specific variants.
-
-### Upcoming research releases:
-
-- **Gilbert-FR-Longform-v1** — extended-speech and meeting optimization  
-- **Gilbert-FR-Accents-v1** — regional and international accent specialization  
-- **Gilbert-FR-Telephone-v1** — 8 kHz telephony channel adaptation  
-- **Gilbert-Edu-ASR-v1** — education-specific speech model  
-- **Gilbert-Multilingual-v1** — French-centric multilingual enhancement  
-
----
-
-## 4. Baseline Performance (WER)
-
-| Dataset | WER |
-|--------|------|
-| MLS (FR) | **3.98%** |
-| Common Voice v13 (FR) | **7.28%** |
-| VoxPopuli (FR) | **8.91%** |
-| Fleurs (FR) | **4.84%** |
-| African-accent French | **4.20%** |
-
-These results position Gilbert-FR among the strongest open-source ASR models available for the French language.
-
----
-
-## 5. Research Principles
-
-1. **Reproducibility**  
-2. **Scientific rigor**  
-3. **Transparent evaluation**  
-4. **Sovereign infrastructure**  
-5. **Operational relevance**  
-
----
-
-## 6. Contact
-
-- Website: **https://gilbert-assistant.fr**  
-- Contact: **mathis@lexiapro.fr**
+- enabling deployment on sovereign infrastructures with strict data governance constraints.