Upgrade OpenAI Whisper to v20231106 (large-v3)

CHANGELOG.md

@@ -4,6 +4,12 @@ Changelog
 Unreleased
 ----------
 
+### Changed
+
+- Upgraded
+    - [openai/whisper](https://github.com/openai/whisper) to [v20231106](https://github.com/openai/whisper/releases/tag/v20231106)
+    
+
 [1.2.2] (2023-11-03)
 --------------------
 

README.md

@@ -9,7 +9,7 @@ Whisper is a general-purpose speech recognition model. It is trained on a large
 ## Features
 Current release (v1.2.2) supports following whisper models:
 
-- [openai/whisper](https://github.com/openai/whisper)@[v20230918](https://github.com/openai/whisper/releases/tag/v20230918)
+- [openai/whisper](https://github.com/openai/whisper)@[v20231106](https://github.com/openai/whisper/releases/tag/v20231106)
 - [guillaumekln/faster-whisper](https://github.com/guillaumekln/faster-whisper)@[0.9.0](https://github.com/guillaumekln/faster-whisper/releases/tag/v0.9.0)
 
 

docs/environmental-variables.md

@@ -15,7 +15,7 @@
 export ASR_MODEL=base
 ```
 
-Available ASR_MODELs are `tiny`, `base`, `small`, `medium`, `large` (only OpenAI Whisper), `large-v1` and `large-v2`. Please note that `large` and `large-v2` are the same model.
+Available ASR_MODELs are `tiny`, `base`, `small`, `medium`, `large` (only OpenAI Whisper), `large-v1`, `large-v2` and `large-v3` (only OpenAI Whisper for now). 
 
 For English-only applications, the `.en` models tend to perform better, especially for the `tiny.en` and `base.en` models. We observed that the difference becomes less significant for the `small.en` and `medium.en` models.
 

docs/index.md

@@ -3,7 +3,7 @@ Whisper is a general-purpose speech recognition model. It is trained on a large
 ## Features
 Current release (v1.2.2) supports following whisper models:
 
-- [openai/whisper](https://github.com/openai/whisper)@[v20230918](https://github.com/openai/whisper/releases/tag/v20230918)
+- [openai/whisper](https://github.com/openai/whisper)@[v20231106](https://github.com/openai/whisper/releases/tag/v20231106)
 - [guillaumekln/faster-whisper](https://github.com/guillaumekln/faster-whisper)@[0.9.0](https://github.com/guillaumekln/faster-whisper/releases/tag/v0.9.0)
 
 ## Quick Usage

poetry.lock

@@ -757,19 +757,19 @@ sympy = "*"
 
 [[package]]
 name = "openai-whisper"
-version = "20230918"
+version = "20231106"
 description = "Robust Speech Recognition via Large-Scale Weak Supervision"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "openai-whisper-20230918.tar.gz", hash = "sha256:32a1ee39c3faaf6c719e3a83f1aacc8e164aad87976350371e26845271287c30"},
+    {file = "openai-whisper-20231106.tar.gz", hash = "sha256:9d1de7fa1e766b9adf8be4bfa7fb11e2bdf8d2b0bf77b90478cf4d75e0e58d19"},
 ]
 
 [package.dependencies]
 more-itertools = "*"
 numba = "*"
 numpy = "*"
-tiktoken = "0.3.3"
+tiktoken = "*"
 torch = "*"
 tqdm = "*"
 
@@ -1574,4 +1574,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "7ba666ad744fc80fff978862f014431c8a03565c7d1b6a459bc759ace4f73078"
+content-hash = "d4773fb3718894fe55d566f19e641fd7bd9be1516788eca099c32cd10c4bd0df"

pyproject.toml

@@ -26,7 +26,7 @@ ffmpeg-python = "^0.2.0"
 fastapi = "^0.104.1"
 llvmlite = "^0.41.1"
 numba = "^0.58.0"
-openai-whisper = "20230918"
+openai-whisper = "20231106"
 faster-whisper = "^0.9.0"
 torch = [
   {markers = "sys_platform == 'darwin' and platform_machine == 'arm64'", url = "https://download.pytorch.org/whl/cpu/torch-1.13.0-cp310-none-macosx_11_0_arm64.whl"},