Update README.md

README.md

@@ -65,7 +65,7 @@ The model is particularly well-suited for applications requiring detailed transc
 
 ### Word Error Rate (WER) Comparison with Whisper Large V3 on LangAge and ESLO (containing interjections, hesitations etc.)
 
-| Dataset Category | Sample Size | Whisper Large V3 | FrisperWhisper | Improvement |
+| Dataset Category | Sample Size | Whisper Large V3 | FrWhisper | Improvement |
 |-----------------|-------------|------------------|----------------|-------------|
 | **All Data** | 196,923 | 99.08% | **84.90%** | **14.18pp** |
 | **LangAge Only** | 69,176 | 78.43% | **67.21%** | **11.22pp** |
@@ -141,7 +141,7 @@ Unlike standard ASR models, FrWhisper will include natural speech elements:
 
 **Standard Whisper**: `"Alors je vais commencer par des petites questions tout à fait simples n'est-ce pas"`
 
-**FrisperWhisper**: `"euh alors je vais commencer par des petites questions tout à fait simples n'est-ce pas"`
+**FrWhisper**: `"euh alors je vais commencer par des petites questions tout à fait simples n'est-ce pas"`
 
 ## Intended Use Cases
 
@@ -160,8 +160,8 @@ Unlike standard ASR models, FrWhisper will include natural speech elements:
 If you use this model in your research, please cite:
 
 ```bibtex
-@misc{frisperwhisper2025,
-  title={FrisperWhisper: Fine-tuned Whisper for French Conversational Speech with Interjections},
+@misc{frwhisper2025,
+  title={FrWhisper: Fine-tuned Whisper for French Conversational Speech with Interjections},
   author={Hanno Müller, Annette Gerstenberg},
   year={2025}
 }