diff --git a/libs/langchain/langchain/document_loaders/parsers/audio.py b/libs/langchain/langchain/document_loaders/parsers/audio.py
index 787bf7a279..fe394570a0 100644
--- a/libs/langchain/langchain/document_loaders/parsers/audio.py
+++ b/libs/langchain/langchain/document_loaders/parsers/audio.py
@@ -1,10 +1,13 @@
+import logging
 import time
-from typing import Iterator, Optional
+from typing import Dict, Iterator, Optional, Tuple
 
 from langchain.document_loaders.base import BaseBlobParser
 from langchain.document_loaders.blob_loaders import Blob
 from langchain.schema import Document
 
+logger = logging.getLogger(__name__)
+
 
 class OpenAIWhisperParser(BaseBlobParser):
     """Transcribe and parse audio files.
@@ -77,12 +80,31 @@ class OpenAIWhisperParser(BaseBlobParser):
 
 class OpenAIWhisperParserLocal(BaseBlobParser):
     """Transcribe and parse audio files.
-    Audio transcription is with OpenAI Whisper model locally from transformers
-    NOTE: By default uses the gpu if available, if you want to use cpu,
-    please set device = "cpu"
+    Audio transcription with OpenAI Whisper model locally from transformers
+    Parameters:
+    device - device to use
+        NOTE: By default uses the gpu if available,
+        if you want to use cpu, please set device = "cpu"
+    lang_model - whisper model to use, for example "openai/whisper-medium"
+    forced_decoder_ids - id states for decoder in multilanguage model,
+        usage example:
+        from transformers import WhisperProcessor
+        processor = WhisperProcessor.from_pretrained("openai/whisper-medium")
+        forced_decoder_ids = WhisperProcessor.get_decoder_prompt_ids(language="french",
+          task="transcribe")
+        forced_decoder_ids = WhisperProcessor.get_decoder_prompt_ids(language="french",
+        task="translate")
+
+
+
     """
 
-    def __init__(self, device: str = "0", lang_model: Optional[str] = None):
+    def __init__(
+        self,
+        device: str = "0",
+        lang_model: Optional[str] = None,
+        forced_decoder_ids: Optional[Tuple[Dict]] = None,
+    ):
         try:
             from transformers import pipeline
         except ImportError:
@@ -136,10 +158,19 @@ class OpenAIWhisperParserLocal(BaseBlobParser):
         # load model for inference
         self.pipe = pipeline(
             "automatic-speech-recognition",
-            model="openai/whisper-medium",
+            model=self.lang_model,
             chunk_length_s=30,
             device=self.device,
         )
+        if forced_decoder_ids is not None:
+            try:
+                self.pipe.model.config.forced_decoder_ids = forced_decoder_ids
+            except Exception as exception_text:
+                logger.info(
+                    "Unable to set forced_decoder_ids parameter for whisper model"
+                    f"Text of exception: {exception_text}"
+                    "Therefore whisper model will use default mode for decoder"
+                )
 
     def lazy_parse(self, blob: Blob) -> Iterator[Document]:
         """Lazily parse the blob."""