diff --git a/haystack/components/audio/whisper_local.py b/haystack/components/audio/whisper_local.py
index abef048e8..00f73fe9f 100644
--- a/haystack/components/audio/whisper_local.py
+++ b/haystack/components/audio/whisper_local.py
@@ -16,7 +16,20 @@ with LazyImport("Run 'pip install \"openai-whisper>=20231106\"' to install whisp
 
 
 logger = logging.getLogger(__name__)
-WhisperLocalModel = Literal["tiny", "small", "medium", "large", "large-v2"]
+WhisperLocalModel = Literal[
+    "base",
+    "base.en",
+    "large",
+    "large-v1",
+    "large-v2",
+    "large-v3",
+    "medium",
+    "medium.en",
+    "small",
+    "small.en",
+    "tiny",
+    "tiny.en",
+]
 
 
 @component
@@ -161,25 +174,21 @@ class LocalWhisperTranscriber:
             raise RuntimeError("Model is not loaded, please run 'warm_up()' before calling 'run()'")
 
         return_segments = kwargs.pop("return_segments", False)
-        transcriptions: Dict[Path, Any] = {}
+        transcriptions = {}
+
         for source in sources:
-            if not isinstance(source, ByteStream):
-                path = Path(source)
-                source = ByteStream.from_file_path(path)
-                source.meta["file_path"] = path
-            else:
-                # If we received a ByteStream instance that doesn't have the "file_path" metadata set,
-                # we dump the bytes into a temporary file.
-                path = source.meta.get("file_path")
-                if path is None:
-                    fp = tempfile.NamedTemporaryFile(delete=False)
+            path = Path(source) if not isinstance(source, ByteStream) else source.meta.get("file_path")
+
+            if isinstance(source, ByteStream) and path is None:
+                with tempfile.NamedTemporaryFile(delete=False) as fp:
                     path = Path(fp.name)
                     source.to_file(path)
-                    source.meta["file_path"] = path
 
             transcription = self._model.transcribe(str(path), **kwargs)
+
             if not return_segments:
                 transcription.pop("segments", None)
+
             transcriptions[path] = transcription
 
         return transcriptions
diff --git a/test/components/audio/test_whisper_local.py b/test/components/audio/test_whisper_local.py
index 6cbd43575..ee2c07c31 100644
--- a/test/components/audio/test_whisper_local.py
+++ b/test/components/audio/test_whisper_local.py
@@ -8,6 +8,8 @@ from unittest.mock import patch, MagicMock
 import pytest
 import torch
 
+from haystack import Pipeline
+from haystack.components.fetchers import LinkContentFetcher
 from haystack.dataclasses import Document, ByteStream
 from haystack.components.audio import LocalWhisperTranscriber
 from haystack.utils.device import ComponentDevice, Device
@@ -169,7 +171,7 @@ class TestLocalWhisperTranscriber:
     @pytest.mark.integration
     @pytest.mark.skipif(sys.platform in ["win32", "cygwin"], reason="ffmpeg not installed on Windows CI")
     def test_whisper_local_transcriber(self, test_files_path):
-        comp = LocalWhisperTranscriber(model="medium", whisper_params={"language": "english"})
+        comp = LocalWhisperTranscriber(model="tiny", whisper_params={"language": "english"})
         comp.warm_up()
         output = comp.run(
             sources=[
@@ -181,13 +183,34 @@ class TestLocalWhisperTranscriber:
         docs = output["documents"]
         assert len(docs) == 3
 
-        assert docs[0].content.strip().lower() == "this is the content of the document."
+        assert all(
+            word in docs[0].content.strip().lower() for word in {"content", "the", "document"}
+        ), f"Expected words not found in: {docs[0].content.strip().lower()}"
         assert test_files_path / "audio" / "this is the content of the document.wav" == docs[0].meta["audio_file"]
 
-        assert docs[1].content.strip().lower() == "the context for this answer is here."
+        assert all(
+            word in docs[1].content.strip().lower() for word in {"context", "answer"}
+        ), f"Expected words not found in: {docs[1].content.strip().lower()}"
         path = test_files_path / "audio" / "the context for this answer is here.wav"
         assert path.absolute() == docs[1].meta["audio_file"]
 
         assert docs[2].content.strip().lower() == "answer."
         # meta.audio_file should contain the temp path where we dumped the audio bytes
         assert docs[2].meta["audio_file"]
+
+    @pytest.mark.integration
+    @pytest.mark.skipif(sys.platform in ["win32", "cygwin"], reason="ffmpeg not installed on Windows CI")
+    def test_whisper_local_transcriber_pipeline_and_url_source(self):
+        pipe = Pipeline()
+        pipe.add_component("fetcher", LinkContentFetcher())
+        pipe.add_component("transcriber", LocalWhisperTranscriber(model="tiny"))
+
+        pipe.connect("fetcher", "transcriber")
+        result = pipe.run(
+            data={
+                "fetcher": {
+                    "urls": ["https://ia903102.us.archive.org/19/items/100-Best--Speeches/EK_19690725_64kb.mp3"]
+                }
+            }
+        )
+        assert "Massachusetts" in result["transcriber"]["documents"][0].content
diff --git a/test/components/audio/test_whisper_remote.py b/test/components/audio/test_whisper_remote.py
index 69c001159..f543d3305 100644
--- a/test/components/audio/test_whisper_remote.py
+++ b/test/components/audio/test_whisper_remote.py
@@ -4,7 +4,10 @@
 import os
 import pytest
 
+from haystack import Pipeline
+from haystack.components.audio import LocalWhisperTranscriber
 from haystack.components.audio.whisper_remote import RemoteWhisperTranscriber
+from haystack.components.fetchers import LinkContentFetcher
 from haystack.dataclasses import ByteStream
 from haystack.utils import Secret
 
@@ -186,3 +189,19 @@ class TestRemoteWhisperTranscriber:
         assert str(test_files_path / "audio" / "the context for this answer is here.wav") == docs[1].meta["file_path"]
 
         assert docs[2].content.strip().lower() == "answer."
+
+    @pytest.mark.integration
+    def test_whisper_local_transcriber_pipeline_and_url_source(self):
+        pipe = Pipeline()
+        pipe.add_component("fetcher", LinkContentFetcher())
+        pipe.add_component("transcriber", RemoteWhisperTranscriber())
+
+        pipe.connect("fetcher", "transcriber")
+        result = pipe.run(
+            data={
+                "fetcher": {
+                    "urls": ["https://ia903102.us.archive.org/19/items/100-Best--Speeches/EK_19690725_64kb.mp3"]
+                }
+            }
+        )
+        assert "Massachusetts" in result["transcriber"]["documents"][0].content