From 6187d25a440e6aba916995b01ff5a4d3af894045 Mon Sep 17 00:00:00 2001
From: Barabazs <31799121+Barabazs@users.noreply.github.com>
Date: Fri, 13 Feb 2026 21:52:32 +0100
Subject: [PATCH] feat: migrate to pyannote-audio v4 with
 speaker-diarization-community-1 (#1349)

* feat: upgrade pyannote-audio dependency to v4

* fix: rename use_auth_token to token for pyannote-audio v4 compatibility

* fix: add omegaconf dep

* fix: use structured output API for pyannote-audio v4 diarization

pyannote-audio 4.x no longer returns a plain Annotation (or tuple when>
return_embeddings=True). It now returns a structured output with
speaker_diarization and speaker_embeddings attributes.

* feat: switch default diarization model to speaker-diarization-community-1

Update default from pyannote/speaker-diarization-3.1 to
pyannote/speaker-diarization-community-1 (pyannote-audio v4),
add CC-BY-4.0 attribution, and update README for v4 API changes.

* fix: correct markdown link formatting for silero-vad in README.md

* chore: update version to 3.8.0


Co-authored-by: Giorgio Azzinnaro <giorgio@azzinna.ro>
---
 README.md                 |  11 +-
 pyproject.toml            |  11 +-
 uv.lock                   | 575 +++++++++++++++++---------------------
 whisperx/__main__.py      |   2 +-
 whisperx/asr.py           |   2 +-
 whisperx/diarize.py       |  31 +-
 whisperx/transcribe.py    |   2 +-
 whisperx/vads/pyannote.py |  12 +-
 8 files changed, 286 insertions(+), 360 deletions(-)

diff --git a/README.md b/README.md
index fae1e0753..fe8610357 100644
--- a/README.md
+++ b/README.md
@@ -113,10 +113,7 @@ You may also need to install ffmpeg, rust etc. Follow openAI instructions here h
 
 ### Speaker Diarization
 
-To **enable Speaker Diarization**, include your Hugging Face access token (read) that you can generate from [Here](https://huggingface.co/settings/tokens) after the `--hf_token` argument and accept the user agreement for the following models: [Segmentation](https://huggingface.co/pyannote/segmentation-3.0) and [Speaker-Diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) (if you choose to use Speaker-Diarization 2.x, follow requirements [here](https://huggingface.co/pyannote/speaker-diarization) instead.)
-
-> **Note**<br>
-> As of Oct 11, 2023, there is a known issue regarding slow performance with pyannote/Speaker-Diarization-3.0 in whisperX. It is due to dependency conflicts between faster-whisper and pyannote-audio 3.0.0. Please see [this issue](https://github.com/m-bain/whisperX/issues/499) for more details and potential workarounds.
+To **enable Speaker Diarization**, include your Hugging Face access token (read) that you can generate from [Here](https://huggingface.co/settings/tokens) after the `--hf_token` argument and accept the user agreement for the [speaker-diarization-community-1](https://huggingface.co/pyannote/speaker-diarization-community-1) model.
 
 <h2 align="left" id="example">Usage 💬 (command line)</h2>
 
@@ -197,7 +194,7 @@ print(result["segments"]) # after alignment
 # import gc; import torch; gc.collect(); torch.cuda.empty_cache(); del model_a
 
 # 3. Assign speaker labels
-diarize_model = DiarizationPipeline(use_auth_token=YOUR_HF_TOKEN, device=device)
+diarize_model = DiarizationPipeline(token=YOUR_HF_TOKEN, device=device)
 
 # add min/max number of speakers if known
 diarize_segments = diarize_model(audio)
@@ -291,8 +288,8 @@ And uses the wonderful pyannote VAD / Diarization https://github.com/pyannote/py
 
 Valuable VAD & Diarization Models from:
 
-- [pyannote audio][https://github.com/pyannote/pyannote-audio]
-- [silero vad][https://github.com/snakers4/silero-vad]
+- [pyannote-audio](https://github.com/pyannote/pyannote-audio) — Speaker diarization powered by the [speaker-diarization-community-1](https://huggingface.co/pyannote/speaker-diarization-community-1) model, licensed under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) by [pyannoteAI](https://www.pyannote.ai)
+- [silero-vad](https://github.com/snakers4/silero-vad)
 
 Great backend from [faster-whisper](https://github.com/guillaumekln/faster-whisper) and [CTranslate2](https://github.com/OpenNMT/CTranslate2)
 
diff --git a/pyproject.toml b/pyproject.toml
index f885d42c2..61dc5df44 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -2,7 +2,7 @@
 urls = { repository = "https://github.com/m-bain/whisperx" }
 authors = [{ name = "Max Bain" }]
 name = "whisperx"
-version = "3.7.7"
+version = "3.8.0"
 description = "Time-Accurate Automatic Speech Recognition using Whisper."
 readme = "README.md"
 requires-python = ">=3.10, <3.14"
@@ -13,8 +13,9 @@ dependencies = [
     "faster-whisper>=1.1.1",
     "nltk>=3.9.1",
     "numpy>=2.1.0",
+    "omegaconf>=2.3.0",
     "pandas>=2.2.3",
-    "pyannote-audio>=3.3.2,<4.0.0",
+    "pyannote-audio>=4.0.0",
     "huggingface-hub<1.0.0",
     "torch~=2.8.0",
     "torchaudio~=2.8.0",
@@ -36,6 +37,12 @@ include-package-data = true
 where = ["."]
 include = ["whisperx*"]
 
+# torchcodec (transitive dep of pyannote-audio >=4) has no wheels for Linux aarch64
+[tool.uv]
+override-dependencies = [
+    "torchcodec>=0.6.0; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'darwin' or sys_platform == 'win32'",
+]
+
 [tool.uv.sources]
 torch = [
   { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" },
diff --git a/uv.lock b/uv.lock
index 59a723a0e..66992af56 100644
--- a/uv.lock
+++ b/uv.lock
@@ -20,6 +20,9 @@ resolution-markers = [
     "python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'",
 ]
 
+[manifest]
+overrides = [{ name = "torchcodec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'", specifier = ">=0.6.0" }]
+
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
@@ -228,66 +231,6 @@ wheels = [
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 ]
 
-[[package]]
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-version = "2.0.0"
-source = { registry = "https://pypi.org/simple" }
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-    { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" },
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-    { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" },
-    { name = "tqdm" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/ab/10/87e666544a4e0cec7cbdc09f26948994831ae0f8bbc58de3bf53b68285ff/speechbrain-1.0.3.tar.gz", hash = "sha256:fcab3c6e90012cecb1eed40ea235733b550137e73da6bfa2340ba191ec714052", size = 747735, upload-time = "2025-04-07T17:17:06.749Z" }
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-
 [[package]]
 name = "sqlalchemy"
 version = "2.0.43"
@@ -2657,29 +2594,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a2/09/77d55d46fd61b4a135c444fc97158ef34a095e5681d0a6c10b75bf356191/sympy-1.14.0-py3-none-any.whl", hash = "sha256:e091cc3e99d2141a0ba2847328f5479b05d94a6635cb96148ccb3f34671bd8f5", size = 6299353, upload-time = "2025-04-27T18:04:59.103Z" },
 ]
 
-[[package]]
-name = "tabulate"
-version = "0.9.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/ec/fe/802052aecb21e3797b8f7902564ab6ea0d60ff8ca23952079064155d1ae1/tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c", size = 81090, upload-time = "2022-10-06T17:21:48.54Z" }
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-
-[[package]]
-name = "tensorboardx"
-version = "2.6.4"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "numpy" },
-    { name = "packaging" },
-    { name = "protobuf" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/2b/c5/d4cc6e293fb837aaf9f76dd7745476aeba8ef7ef5146c3b3f9ee375fe7a5/tensorboardx-2.6.4.tar.gz", hash = "sha256:b163ccb7798b31100b9f5fa4d6bc22dad362d7065c2f24b51e50731adde86828", size = 4769801, upload-time = "2025-06-10T22:37:07.419Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/e0/1d/b5d63f1a6b824282b57f7b581810d20b7a28ca951f2d5b59f1eb0782c12b/tensorboardx-2.6.4-py3-none-any.whl", hash = "sha256:5970cf3a1f0a6a6e8b180ccf46f3fe832b8a25a70b86e5a237048a7c0beb18e2", size = 87201, upload-time = "2025-06-10T22:37:05.44Z" },
-]
-
 [[package]]
 name = "threadpoolctl"
 version = "3.6.0"
@@ -2999,6 +2913,25 @@ wheels = [
     { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp313-cp313t-win_amd64.whl", hash = "sha256:1054e0a7613cac54ed9b3784a5fcbe023748a70004d9cca74c5f9ae00a1fdfd1" },
 ]
 
+[[package]]
+name = "torchcodec"
+version = "0.10.0"
+source = { registry = "https://pypi.org/simple" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d0/1c/549e79c0f5a7e48c1f767b648c3ea3301a8cd702f66c9cb32c86eb347d63/torchcodec-0.10.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a2ecb3e38414a9326ffca56e49a05a9f513813aa118b7f540110d09ab725d1f7", size = 3406242, upload-time = "2026-01-22T15:41:42.056Z" },
+    { url = "https://files.pythonhosted.org/packages/f0/47/041180c095e4dbc0cff8e847974bf400114379c8f114aa8c3c96e9d6bd4e/torchcodec-0.10.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:61f9b12fcd5b89d5e7e874c5feeb7c2c99821868a32f6ebbf6e8692409b2b6f7", size = 2062569, upload-time = "2026-01-22T15:41:34.99Z" },
+    { url = "https://files.pythonhosted.org/packages/dc/51/b7c339cabf375789fc74b56006fe6bc5e029ededf83bc7629864cb6ed083/torchcodec-0.10.0-cp310-cp310-win_amd64.whl", hash = "sha256:a49e3ebab65e559a98af6f63371a837f69b8542059da8def30bd6e658c5e86d3", size = 2208079, upload-time = "2026-01-22T15:41:49.866Z" },
+    { url = "https://files.pythonhosted.org/packages/1c/0d/51ab5cb4ba8eb60e3e39651a4d43be89a592cc193fe11feb6509509b0121/torchcodec-0.10.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3dde1ebd9677ec1587f1e45486b3d59bd3e41a0bf4fc9b3dc6880e64c421ad56", size = 3907950, upload-time = "2026-01-22T15:41:43.819Z" },
+    { url = "https://files.pythonhosted.org/packages/b9/c8/618bde55c1908583290883537326174e633a383a8337226ce0c7c6d70090/torchcodec-0.10.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:2e2be11c4468a58940572fcf5f8ed5e41187c1de214267f692e2fd5ac8731198", size = 2070483, upload-time = "2026-01-22T15:41:36.743Z" },
+    { url = "https://files.pythonhosted.org/packages/74/f1/75d70391de0581069864b3c204bb7e463a2b3b32e840ff9d103688a6db94/torchcodec-0.10.0-cp311-cp311-win_amd64.whl", hash = "sha256:f51d9435d3c75c0b55f5dc64a22ce9cfb58ac19013cdd8ce572a523ef75e2b58", size = 2219702, upload-time = "2026-01-22T15:41:50.933Z" },
+    { url = "https://files.pythonhosted.org/packages/52/ff/2b27797e039673156710e5a0febe87cafc203722acafa3d34db283b40cf9/torchcodec-0.10.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b35fa4061c5757f8d714187c040a90a11669de6470a644bb04e3cd335ff1c110", size = 4073213, upload-time = "2026-01-22T15:41:45.485Z" },
+    { url = "https://files.pythonhosted.org/packages/29/34/ccc711b6dc581e43b8d8d227e4173a8826994ee7b68d6b3d82291f307325/torchcodec-0.10.0-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:6e43184d83ccced965b31cad5bb6200c779646fee2ec153a6d784b4def40c91b", size = 2083121, upload-time = "2026-01-22T15:41:37.947Z" },
+    { url = "https://files.pythonhosted.org/packages/cf/6c/9af3bd945a610d6c757d898aa4624e0f5135cc8a6992d0a1d846f1084576/torchcodec-0.10.0-cp312-cp312-win_amd64.whl", hash = "sha256:e4f022fa53d91b414b4177fe87b0afc40a806092da4595d24de4b245d6fb0fba", size = 2225338, upload-time = "2026-01-22T15:41:52.094Z" },
+    { url = "https://files.pythonhosted.org/packages/d2/b6/b1041c8ccb175b08779b3e2d3e60f838bbcbfe2398d49e3673b6a66f0649/torchcodec-0.10.0-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:be3ce7cc667effecd06da9d0d6c5e9e347c5f376b705934e7b82378a65cf6eef", size = 4043681, upload-time = "2026-01-22T15:41:47.236Z" },
+    { url = "https://files.pythonhosted.org/packages/fd/85/fc44f6d702dfd344e6859a9a4d713aaaa991578eb74677a80297d9ae8a07/torchcodec-0.10.0-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:71f25caf9ab89a434ae2008b1374fd98557a6864b8313b103bae53af3e6fd17f", size = 2088572, upload-time = "2026-01-22T15:41:39.203Z" },
+    { url = "https://files.pythonhosted.org/packages/df/9d/b73a0f47e11b66a1d23c7d867f12f8bb41b1b5e707d7e23d8f54793e3267/torchcodec-0.10.0-cp313-cp313-win_amd64.whl", hash = "sha256:9e077146e894f373b805972da96aee42ff8bb87b1a3f3fb64d26925cd9e64184", size = 2225208, upload-time = "2026-01-22T15:41:53.233Z" },
+]
+
 [[package]]
 name = "torchmetrics"
 version = "1.8.2"
@@ -3064,21 +2997,6 @@ wheels = [
     { url = "https://download.pytorch.org/whl/triton-3.4.0-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5f2f15de16fefacac008378919687c0ada6a867dcc0fe70a5d5a11240ae8b814" },
 ]
 
-[[package]]
-name = "typer"
-version = "0.19.2"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "click" },
-    { name = "rich" },
-    { name = "shellingham" },
-    { name = "typing-extensions" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/21/ca/950278884e2ca20547ff3eb109478c6baf6b8cf219318e6bc4f666fad8e8/typer-0.19.2.tar.gz", hash = "sha256:9ad824308ded0ad06cc716434705f691d4ee0bfd0fb081839d2e426860e7fdca", size = 104755, upload-time = "2025-09-23T09:47:48.256Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/00/22/35617eee79080a5d071d0f14ad698d325ee6b3bf824fc0467c03b30e7fa8/typer-0.19.2-py3-none-any.whl", hash = "sha256:755e7e19670ffad8283db353267cb81ef252f595aa6834a0d1ca9312d9326cb9", size = 46748, upload-time = "2025-09-23T09:47:46.777Z" },
-]
-
 [[package]]
 name = "typing-extensions"
 version = "4.15.0"
@@ -3108,7 +3026,7 @@ wheels = [
 
 [[package]]
 name = "whisperx"
-version = "3.7.7"
+version = "3.8.0"
 source = { editable = "." }
 dependencies = [
     { name = "ctranslate2" },
@@ -3116,6 +3034,7 @@ dependencies = [
     { name = "huggingface-hub" },
     { name = "nltk" },
     { name = "numpy" },
+    { name = "omegaconf" },
     { name = "pandas" },
     { name = "pyannote-audio" },
     { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" },
@@ -3135,8 +3054,9 @@ requires-dist = [
     { name = "huggingface-hub", specifier = "<1.0.0" },
     { name = "nltk", specifier = ">=3.9.1" },
     { name = "numpy", specifier = ">=2.1.0" },
+    { name = "omegaconf", specifier = ">=2.3.0" },
     { name = "pandas", specifier = ">=2.2.3" },
-    { name = "pyannote-audio", specifier = ">=3.3.2,<4.0.0" },
+    { name = "pyannote-audio", specifier = ">=4.0.0" },
     { name = "torch", marker = "sys_platform == 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" },
     { name = "torch", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" },
     { name = "torch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" },
@@ -3245,3 +3165,12 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/94/c3/b2e9f38bc3e11191981d57ea08cab2166e74ea770024a646617c9cddd9f6/yarl-1.20.1-cp313-cp313t-win_amd64.whl", hash = "sha256:541d050a355bbbc27e55d906bc91cb6fe42f96c01413dd0f4ed5a5240513874f", size = 93003, upload-time = "2025-06-10T00:45:27.752Z" },
     { url = "https://files.pythonhosted.org/packages/b4/2d/2345fce04cfd4bee161bf1e7d9cdc702e3e16109021035dbb24db654a622/yarl-1.20.1-py3-none-any.whl", hash = "sha256:83b8eb083fe4683c6115795d9fc1cfaf2cbbefb19b3a1cb68f6527460f483a77", size = 46542, upload-time = "2025-06-10T00:46:07.521Z" },
 ]
+
+[[package]]
+name = "zipp"
+version = "3.23.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/e3/02/0f2892c661036d50ede074e376733dca2ae7c6eb617489437771209d4180/zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166", size = 25547, upload-time = "2025-06-08T17:06:39.4Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/2e/54/647ade08bf0db230bfea292f893923872fd20be6ac6f53b2b936ba839d75/zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e", size = 10276, upload-time = "2025-06-08T17:06:38.034Z" },
+]
diff --git a/whisperx/__main__.py b/whisperx/__main__.py
index e7cc62f0e..dbb92fc4f 100644
--- a/whisperx/__main__.py
+++ b/whisperx/__main__.py
@@ -45,7 +45,7 @@ def cli():
     parser.add_argument("--diarize", action="store_true", help="Apply diarization to assign speaker labels to each segment/word")
     parser.add_argument("--min_speakers", default=None, type=int, help="Minimum number of speakers to in audio file")
     parser.add_argument("--max_speakers", default=None, type=int, help="Maximum number of speakers to in audio file")
-    parser.add_argument("--diarize_model", default="pyannote/speaker-diarization-3.1", type=str, help="Name of the speaker diarization model to use")
+    parser.add_argument("--diarize_model", default="pyannote/speaker-diarization-community-1", type=str, help="Name of the speaker diarization model to use")
     parser.add_argument("--speaker_embeddings", action="store_true", help="Include speaker embeddings in JSON output (only works with --diarize)")
 
     parser.add_argument("--temperature", type=float, default=0, help="temperature to use for sampling")
diff --git a/whisperx/asr.py b/whisperx/asr.py
index bddc0b78c..f9456be8a 100644
--- a/whisperx/asr.py
+++ b/whisperx/asr.py
@@ -407,7 +407,7 @@ def load_model(
                 device_vad = f'cuda:{device_index}'
             else:
                 device_vad = device
-            vad_model = Pyannote(torch.device(device_vad), use_auth_token=None, **default_vad_options)
+            vad_model = Pyannote(torch.device(device_vad), token=None, **default_vad_options)
         else:
             raise ValueError(f"Invalid vad_method: {vad_method}")
 
diff --git a/whisperx/diarize.py b/whisperx/diarize.py
index 1b2e29600..59b0f2f1b 100644
--- a/whisperx/diarize.py
+++ b/whisperx/diarize.py
@@ -92,14 +92,14 @@ class DiarizationPipeline:
     def __init__(
         self,
         model_name=None,
-        use_auth_token=None,
+        token=None,
         device: Optional[Union[str, torch.device]] = "cpu",
     ):
         if isinstance(device, str):
             device = torch.device(device)
-        model_config = model_name or "pyannote/speaker-diarization-3.1"
+        model_config = model_name or "pyannote/speaker-diarization-community-1"
         logger.info(f"Loading diarization model: {model_config}")
-        self.model = Pipeline.from_pretrained(model_config, use_auth_token=use_auth_token).to(device)
+        self.model = Pipeline.from_pretrained(model_config, token=token).to(device)
 
     def __call__(
         self,
@@ -132,22 +132,15 @@ def __call__(
             'sample_rate': SAMPLE_RATE
         }
 
-        if return_embeddings:
-            diarization, embeddings = self.model(
-                audio_data,
-                num_speakers=num_speakers,
-                min_speakers=min_speakers,
-                max_speakers=max_speakers,
-                return_embeddings=True,
-            )
-        else:
-            diarization = self.model(
-                audio_data,
-                num_speakers=num_speakers,
-                min_speakers=min_speakers,
-                max_speakers=max_speakers,
-            )
-            embeddings = None
+        output = self.model(
+            audio_data,
+            num_speakers=num_speakers,
+            min_speakers=min_speakers,
+            max_speakers=max_speakers,
+        )
+
+        diarization = output.speaker_diarization
+        embeddings = output.speaker_embeddings if return_embeddings else None
 
         diarize_df = pd.DataFrame(diarization.itertracks(yield_label=True), columns=['segment', 'label', 'speaker'])
         diarize_df['start'] = diarize_df['segment'].apply(lambda x: x.start)
diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py
index 04c2ab368..0aae410c8 100644
--- a/whisperx/transcribe.py
+++ b/whisperx/transcribe.py
@@ -214,7 +214,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser):
         logger.info("Performing diarization...")
         logger.info(f"Using model: {diarize_model_name}")
         results = []
-        diarize_model = DiarizationPipeline(model_name=diarize_model_name, use_auth_token=hf_token, device=device)
+        diarize_model = DiarizationPipeline(model_name=diarize_model_name, token=hf_token, device=device)
         for result, input_audio_path in tmp_results:
             diarize_result = diarize_model(
                 input_audio_path, 
diff --git a/whisperx/vads/pyannote.py b/whisperx/vads/pyannote.py
index 0e806bb19..28c1fbdf5 100644
--- a/whisperx/vads/pyannote.py
+++ b/whisperx/vads/pyannote.py
@@ -18,7 +18,7 @@
 logger = get_logger(__name__)
 
 
-def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, use_auth_token=None, model_fp=None):
+def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, token=None, model_fp=None):
     model_dir = torch.hub._get_torch_home()
 
     main_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
@@ -40,7 +40,7 @@ def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, use_auth_token=Non
 
     model_bytes = open(model_fp, "rb").read()
 
-    vad_model = Model.from_pretrained(model_fp, use_auth_token=use_auth_token)
+    vad_model = Model.from_pretrained(model_fp, token=token)
     hyperparameters = {"onset": vad_onset,
                     "offset": vad_offset,
                     "min_duration_on": 0.1,
@@ -192,11 +192,11 @@ def __init__(
             self,
             segmentation: PipelineModel = "pyannote/segmentation",
             fscore: bool = False,
-            use_auth_token: Union[Text, None] = None,
+            token: Union[Text, None] = None,
             **inference_kwargs,
     ):
 
-        super().__init__(segmentation=segmentation, fscore=fscore, use_auth_token=use_auth_token, **inference_kwargs)
+        super().__init__(segmentation=segmentation, fscore=fscore, token=token, **inference_kwargs)
 
     def apply(self, file: AudioFile, hook: Optional[Callable] = None) -> Annotation:
         """Apply voice activity detection
@@ -234,10 +234,10 @@ def apply(self, file: AudioFile, hook: Optional[Callable] = None) -> Annotation:
 
 class Pyannote(Vad):
 
-    def __init__(self, device, use_auth_token=None, model_fp=None, **kwargs):
+    def __init__(self, device, token=None, model_fp=None, **kwargs):
         logger.info("Performing voice activity detection using Pyannote...")
         super().__init__(kwargs['vad_onset'])
-        self.vad_pipeline = load_vad_model(device, use_auth_token=use_auth_token, model_fp=model_fp)
+        self.vad_pipeline = load_vad_model(device, token=token, model_fp=model_fp)
 
     def __call__(self, audio: AudioFile, **kwargs):
         return self.vad_pipeline(audio)