Update README.md

README.md

@@ -32,20 +32,26 @@ for segment in segments:
 ```
 
 ### Benchmark
-We measure the inference speed with four different Japanese speech audio on MacBook Pro with the following spec:
+We measure the inference speed of different kotoba-whisper-v1.0 implementations with four different Japanese speech audio on MacBook Pro with the following spec:
 - Apple M2 Pro
 - 32GB
 - 14-inch, 2023
 - OS Sonoma Version 14.4.1 (23E224)
 
-
-
-| audio file | audio duration (min)| inference time (sec) |
-|--|---------------------|-------------|
-|audio 1 | 50.3 | 2601       |
-|audio 2 | 5.6  | 73       |
-|audio 3 | 4.9  | 141       |
-|audio 4 | 5.6  | 126       |
+| audio file | audio duration (min)| [whisper.cpp](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml) (sec) | [faster-whisper](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-faster) (sec)| [hf pipeline](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0) (sec)
+|--------|------|-----|------|-----|
+|audio 1 | 50.3 | 581 | 2601 | 807 |
+|audio 2 | 5.6  | 41  | 73   | 61  |
+|audio 3 | 4.9  | 30  | 141  | 54  |
+|audio 4 | 5.6  | 35  | 126  | 69  |
+
+Scripts to re-run the experiment can be found bellow:
+* [whisper.cpp](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml/blob/main/benchmark.sh)
+* [faster-whisper](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-faster/blob/main/benchmark.sh)
+* [hf pipeline](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0/blob/main/benchmark.sh)
+Also, currently whisper.cpp and faster-whisper support the [sequential long-form decoding](https://huggingface.co/distil-whisper/distil-large-v3#sequential-long-form),
+and only Huggingface pipeline supports the [chunked long-form decoding](https://huggingface.co/distil-whisper/distil-large-v3#chunked-long-form), which we empirically
+ found better than the sequnential long-form decoding.
 
 
 ## Conversion details