diff --git a/alembic/versions/c176288cb508_add_audio_info.py b/alembic/versions/c176288cb508_add_audio_info.py
new file mode 100644
index 000000000..db7de14ae
--- /dev/null
+++ b/alembic/versions/c176288cb508_add_audio_info.py
@@ -0,0 +1,47 @@
+"""Add audio info.
+
+Revision ID: c176288cb508
+Revises: 8713b142f5de
+Create Date: 2023-08-31 00:25:04.889325
+
+"""
+import sqlalchemy as sa
+
+from alembic import op
+from openadapt.models import ForceFloat
+
+# revision identifiers, used by Alembic.
+revision = "c176288cb508"
+down_revision = "8713b142f5de"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table(
+        "audio_info",
+        sa.Column("id", sa.Integer(), nullable=False),
+        sa.Column("flac_data", sa.LargeBinary(), nullable=True),
+        sa.Column("transcribed_text", sa.String(), nullable=True),
+        sa.Column(
+            "recording_timestamp",
+            ForceFloat(precision=10, scale=2, asdecimal=False),
+            nullable=True,
+        ),
+        sa.Column("sample_rate", sa.Integer(), nullable=True),
+        sa.Column("words_with_timestamps", sa.Text(), nullable=True),
+        sa.ForeignKeyConstraint(
+            ["recording_timestamp"],
+            ["recording.timestamp"],
+            name=op.f("fk_audio_info_recording_timestamp_recording"),
+        ),
+        sa.PrimaryKeyConstraint("id", name=op.f("pk_audio_info")),
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table("audio_info")
+    # ### end Alembic commands ###
diff --git a/openadapt/crud.py b/openadapt/crud.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/openadapt/db/crud.py b/openadapt/db/crud.py
index 7b48d9a82..71ad34b74 100644
--- a/openadapt/db/crud.py
+++ b/openadapt/db/crud.py
@@ -4,6 +4,7 @@
 """
 
 from typing import Any
+import json
 
 from loguru import logger
 import sqlalchemy as sa
@@ -12,6 +13,7 @@
 from openadapt.db.db import BaseModel, Session
 from openadapt.models import (
     ActionEvent,
+    AudioInfo,
     MemoryStat,
     PerformanceStat,
     Recording,
@@ -411,3 +413,22 @@ def new_session() -> None:
     if db:
         db.close()
     db = Session()
+
+
+def insert_audio_info(
+    audio_data: bytes,
+    transcribed_text: str,
+    recording_timestamp: float,
+    sample_rate: int,
+    word_list: list,
+) -> None:
+    """Create an AudioInfo entry in the database."""
+    audio_info = AudioInfo(
+        flac_data=audio_data,
+        transcribed_text=transcribed_text,
+        recording_timestamp=recording_timestamp,
+        sample_rate=sample_rate,
+        words_with_timestamps=json.dumps(word_list),
+    )
+    db.add(audio_info)
+    db.commit()
diff --git a/openadapt/db/db.py b/openadapt/db/db.py
index 7a535607e..c507d6e24 100644
--- a/openadapt/db/db.py
+++ b/openadapt/db/db.py
@@ -5,7 +5,7 @@
 
 from dictalchemy import DictableModel
 from sqlalchemy.ext.declarative import declarative_base
-from sqlalchemy.orm import sessionmaker
+from sqlalchemy.orm import scoped_session, sessionmaker
 from sqlalchemy.schema import MetaData
 import sqlalchemy as sa
 
@@ -67,4 +67,5 @@ def get_base(engine: sa.engine) -> sa.engine:
 
 engine = get_engine()
 Base = get_base(engine)
-Session = sessionmaker(bind=engine)
+session_factory = sessionmaker(bind=engine)
+Session = scoped_session(session_factory)
diff --git a/openadapt/models.py b/openadapt/models.py
index f17215d7f..b64f78d95 100644
--- a/openadapt/models.py
+++ b/openadapt/models.py
@@ -61,6 +61,8 @@ class Recording(db.Base):
         order_by="WindowEvent.timestamp",
     )
 
+    audio_info = sa.orm.relationship("AudioInfo", back_populates="recording")
+
     _processed_action_events = None
 
     @property
@@ -378,6 +380,21 @@ def get_active_window_event(cls: "WindowEvent") -> "WindowEvent":
         return WindowEvent(**window.get_active_window_data())
 
 
+class AudioInfo(db.Base):
+    """Class representing the audio from a recording in the database."""
+
+    __tablename__ = "audio_info"
+
+    id = sa.Column(sa.Integer, primary_key=True)
+    flac_data = sa.Column(sa.LargeBinary)
+    transcribed_text = sa.Column(sa.String)
+    recording_timestamp = sa.Column(sa.ForeignKey("recording.timestamp"))
+    sample_rate = sa.Column(sa.Integer)
+    words_with_timestamps = sa.Column(sa.Text)
+
+    recording = sa.orm.relationship("Recording", back_populates="audio_info")
+
+
 class PerformanceStat(db.Base):
     """Class representing a performance statistic in the database."""
 
diff --git a/openadapt/record.py b/openadapt/record.py
index 6b6bb9f63..5165056d9 100644
--- a/openadapt/record.py
+++ b/openadapt/record.py
@@ -4,11 +4,16 @@
 
     $ python openadapt/record.py "<description of task to be recorded>"
 
+To record audio:
+
+    $ python openadapt/record.py "<description of task to be recorded>" --enable_audio
+
 """
 
 from collections import namedtuple
 from functools import partial, wraps
 from typing import Any, Callable, Union
+import io
 import multiprocessing
 import os
 import queue
@@ -24,7 +29,11 @@
 from tqdm import tqdm
 import fire
 import mss.tools
+import numpy as np
 import psutil
+import sounddevice
+import soundfile
+import whisper
 
 from openadapt import config, utils, window
 from openadapt.db import crud
@@ -804,15 +813,101 @@ def read_mouse_events(
     mouse_listener.stop()
 
 
+def record_audio(
+    terminate_event: multiprocessing.Event,
+    recording_timestamp: float,
+) -> None:
+    """Record audio narration during the recording and store data in database.
+
+    Args:
+        terminate_event: The event to signal termination of event reading.
+        recording_timestamp: The timestamp of the recording.
+    """
+    utils.configure_logging(logger, LOG_LEVEL)
+    utils.set_start_time(recording_timestamp)
+
+    audio_frames = []  # to store audio frames
+
+    def audio_callback(
+        indata: np.ndarray, frames: int, time: Any, status: sounddevice.CallbackFlags
+    ) -> None:
+        """Callback function used when new audio frames are recorded.
+
+        Note: time is of type cffi.FFI.CData, but since we don't use this argument
+        and we also don't use the cffi library, the Any type annotation is used.
+        """
+        # called whenever there is new audio frames
+        audio_frames.append(indata.copy())
+
+    # open InputStream and start recording while ActionEvents are recorded
+    audio_stream = sounddevice.InputStream(
+        callback=audio_callback, samplerate=16000, channels=1
+    )
+    logger.info("Audio recording started.")
+    audio_stream.start()
+    terminate_event.wait()
+    audio_stream.stop()
+    audio_stream.close()
+
+    # Concatenate into one Numpy array
+    concatenated_audio = np.concatenate(audio_frames, axis=0)
+    # convert concatenated_audio to format expected by whisper
+    converted_audio = concatenated_audio.flatten().astype(np.float32)
+
+    # Convert audio to text using OpenAI's Whisper
+    logger.info("Transcribing audio...")
+    model = whisper.load_model("base")
+    result_info = model.transcribe(converted_audio, word_timestamps=True, fp16=False)
+    logger.info(f"The narrated text is: {result_info['text']}")
+    # empty word_list if the user didn't say anything
+    word_list = []
+    # segments could be empty
+    if len(result_info["segments"]) > 0:
+        # there won't be a 'words' list if the user didn't say anything
+        if "words" in result_info["segments"][0]:
+            word_list = result_info["segments"][0]["words"]
+
+    # compress and convert to bytes to save to database
+    logger.info(
+        "Size of uncompressed audio data: {} bytes".format(converted_audio.nbytes)
+    )
+    # Create an in-memory file-like object
+    file_obj = io.BytesIO()
+    # Write the audio data using lossless compression
+    soundfile.write(
+        file_obj, converted_audio, int(audio_stream.samplerate), format="FLAC"
+    )
+    # Get the compressed audio data as bytes
+    compressed_audio_bytes = file_obj.getvalue()
+
+    logger.info(
+        "Size of compressed audio data: {} bytes".format(len(compressed_audio_bytes))
+    )
+
+    file_obj.close()
+
+    # To decompress the audio and restore it to its original form:
+    # restored_audio, restored_samplerate = sf.read(
+    # io.BytesIO(compressed_audio_bytes))
+
+    # Create AudioInfo entry
+    crud.insert_audio_info(
+        compressed_audio_bytes,
+        result_info["text"],
+        recording_timestamp,
+        int(audio_stream.samplerate),
+        word_list,
+    )
+
+
 @logger.catch
 @trace(logger)
-def record(
-    task_description: str,
-) -> None:
+def record(task_description: str, enable_audio: bool = False) -> None:
     """Record Screenshots/ActionEvents/WindowEvents.
 
     Args:
         task_description: A text description of the task to be recorded.
+        enable_audio: a flag to enable or disable audio recording (default: False)
     """
     logger.info(f"{task_description=}")
 
@@ -943,6 +1038,13 @@ def record(
         )
         mem_plotter.start()
 
+    if enable_audio:
+        audio_recorder = threading.Thread(
+            target=record_audio,
+            args=(terminate_event, recording_timestamp),
+        )
+        audio_recorder.start()
+
     # TODO: discard events until everything is ready
 
     collect_stats()
@@ -972,6 +1074,9 @@ def record(
     screen_event_writer.join()
     action_event_writer.join()
     window_event_writer.join()
+    if enable_audio:
+        audio_recorder.join()
+
     terminate_perf_event.set()
 
     if PLOT_PERFORMANCE:
diff --git a/openadapt/strategies/mixins/openai.py b/openadapt/strategies/mixins/openai.py
index 35386b87a..3031e310d 100644
--- a/openadapt/strategies/mixins/openai.py
+++ b/openadapt/strategies/mixins/openai.py
@@ -11,7 +11,6 @@ class MyReplayStrategy(OpenAIReplayStrategyMixin):
 
 from loguru import logger
 import openai
-import tiktoken
 
 from openadapt import cache, config, models
 from openadapt.strategies.base import BaseReplayStrategy
@@ -29,7 +28,6 @@ class MyReplayStrategy(OpenAIReplayStrategyMixin):
 MODEL_NAME = "gpt-4"
 
 openai.api_key = config.OPENAI_API_KEY
-encoding = tiktoken.get_encoding("cl100k_base")
 
 
 class OpenAIReplayStrategyMixin(BaseReplayStrategy):
@@ -187,50 +185,3 @@ def _get_completion(prompt: str) -> str:
     logger.debug(f"appending assistant_message=\n{pformat(assistant_message)}")
     messages.append(assistant_message)
     return messages
-
-
-# XXX TODO not currently in use
-# https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
-def num_tokens_from_messages(messages: list, model: str = "gpt-3.5-turbo-0301") -> int:
-    """Returns the number of tokens used by a list of messages."""
-    try:
-        encoding = tiktoken.encoding_for_model(model)
-    except KeyError:
-        logger.info("Warning: model not found. Using cl100k_base encoding.")
-        encoding = tiktoken.get_encoding("cl100k_base")
-    if model == "gpt-3.5-turbo":
-        logger.info(
-            "Warning: gpt-3.5-turbo may change over time. Returning num tokens "
-            "assuming gpt-3.5-turbo-0301."
-        )
-        return num_tokens_from_messages(messages, model="gpt-3.5-turbo-0301")
-    elif model == "gpt-4":
-        logger.info(
-            "Warning: gpt-4 may change over time. Returning num tokens "
-            "assuming gpt-4-0314."
-        )
-        return num_tokens_from_messages(messages, model="gpt-4-0314")
-    elif model == "gpt-3.5-turbo-0301":
-        tokens_per_message = (
-            4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
-        )
-        tokens_per_name = -1  # if there's a name, the role is omitted
-    elif model == "gpt-4-0314":
-        tokens_per_message = 3
-        tokens_per_name = 1
-    else:
-        raise NotImplementedError(
-            f"""num_tokens_from_messages() is not implemented for model "
-            "{model}. See "
-            "https://github.com/openai/openai-python/blob/main/chatml.md for "
-            information on how messages are converted to tokens."""
-        )
-    num_tokens = 0
-    for message in messages:
-        num_tokens += tokens_per_message
-        for key, value in message.items():
-            num_tokens += len(encoding.encode(value))
-            if key == "name":
-                num_tokens += tokens_per_name
-    num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
-    return num_tokens
diff --git a/openadapt/visualize.py b/openadapt/visualize.py
index ecac1906f..d71508790 100644
--- a/openadapt/visualize.py
+++ b/openadapt/visualize.py
@@ -12,7 +12,7 @@
 import click
 
 from openadapt import config
-from openadapt.db.crud import get_latest_recording, get_recording
+from openadapt.db.crud import get_audio_info, get_latest_recording, get_recording
 from openadapt.events import get_events
 from openadapt.utils import (
     EMPTY,
@@ -147,6 +147,10 @@ def main(timestamp: str, notify: bool = True) -> None:
         scrub.scrub_text(recording.task_description)
     logger.debug(f"{recording=}")
 
+    audio_info = row2dict(get_audio_info(recording))
+    # don't display the FLAC data
+    del audio_info["flac_data"]
+
     meta = {}
     action_events = get_events(recording, process=PROCESS_EVENTS, meta=meta)
     event_dicts = rows2dicts(action_events)
diff --git a/poetry.lock b/poetry.lock
index 0e29491ea..53c662c5e 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -175,24 +175,24 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "3.7.1"
+version = "4.0.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
-    {file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
+    {file = "anyio-4.0.0-py3-none-any.whl", hash = "sha256:cfdb2b588b9fc25ede96d8db56ed50848b0b649dca3dd1df0b11f683bb9e0b5f"},
+    {file = "anyio-4.0.0.tar.gz", hash = "sha256:f7ed51751b2c2add651e5747c891b47e26d2a21be5d32d9311dfe9692f3e5d7a"},
 ]
 
 [package.dependencies]
-exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
-test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (<0.22)"]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.22)"]
 
 [[package]]
 name = "appnope"
@@ -430,17 +430,17 @@ typing-extensions = ">=3.10.0"
 
 [[package]]
 name = "boto3"
-version = "1.28.30"
+version = "1.28.38"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "boto3-1.28.30-py3-none-any.whl", hash = "sha256:e095ede98d3680e65966ab71f273b7d86938f5d853773ef96f4cb646277c2a4b"},
-    {file = "boto3-1.28.30.tar.gz", hash = "sha256:2b509a959966a572f15db5768a18066ce1f53022ac53fca9421c620219fa3998"},
+    {file = "boto3-1.28.38-py3-none-any.whl", hash = "sha256:dae0bc5548b39d8dfcf4167d9a238ab899a0491c11c5e77934db71b3ecf34752"},
+    {file = "boto3-1.28.38.tar.gz", hash = "sha256:cdb466e51ebe4c99640269d88d5450328271437d58e6ce089690d0485bef6174"},
 ]
 
 [package.dependencies]
-botocore = ">=1.31.30,<1.32.0"
+botocore = ">=1.31.38,<1.32.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.6.0,<0.7.0"
 
@@ -449,13 +449,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.31.30"
+version = "1.31.38"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "botocore-1.31.30-py3-none-any.whl", hash = "sha256:269f20dcadd8dfd0c26d0e6fbceb84814ff6638ff3aafcc5324b9fb9949a7051"},
-    {file = "botocore-1.31.30.tar.gz", hash = "sha256:3cf6a9d7621b897c9ff23cd02113826141b3dd3d7e90273b661efc4dc05f84e2"},
+    {file = "botocore-1.31.38-py3-none-any.whl", hash = "sha256:86a4c253bba046f775e07f6585ff6c3d75c21a21c171e5bfcf68bc59f29d7b4c"},
+    {file = "botocore-1.31.38.tar.gz", hash = "sha256:b02de7898f0a7de0f6569be1c87046035a974006c31fd641f4b97a8dba1fad21"},
 ]
 
 [package.dependencies]
@@ -2118,6 +2118,39 @@ files = [
 [package.dependencies]
 rapidfuzz = ">=2.3.0,<4.0.0"
 
+[[package]]
+name = "llvmlite"
+version = "0.40.1rc1"
+description = "lightweight wrapper around basic LLVM functionality"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "llvmlite-0.40.1rc1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:31b606ae4923a897fe7122fe9a75fa39713279e796b335b83cb929c5d9e8661b"},
+    {file = "llvmlite-0.40.1rc1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d08de4135dd8652f46de42e795b744dcad8cc11de3b6044a7326a61636887655"},
+    {file = "llvmlite-0.40.1rc1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94043bb283395963b48fa964c776670889084be5117cbc4f831ab357005365d1"},
+    {file = "llvmlite-0.40.1rc1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:659b400cf61e567c5c30159f60eac8562133bf5e497f481388d22e6b5dd00044"},
+    {file = "llvmlite-0.40.1rc1-cp310-cp310-win32.whl", hash = "sha256:84f5c569fdcc503a7ce5018d2115ebac3a385743774ed22c6cc8dade673eae33"},
+    {file = "llvmlite-0.40.1rc1-cp310-cp310-win_amd64.whl", hash = "sha256:a775e87d6ee6f6fcdae5ead0dec171243719002fc39c500c4813babb3609f6d9"},
+    {file = "llvmlite-0.40.1rc1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:239eaeef72267566538b9f4cba8a41fb3e39ac99881c2a9a8100aff60c645edb"},
+    {file = "llvmlite-0.40.1rc1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2b8ceb9c436acdc87c3f5ab2dd6e3d003cf938abf55d3470d059abd99dee63d3"},
+    {file = "llvmlite-0.40.1rc1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0475c5107334cf528c607275e0e1cd7836c31fe07c6e45994cd02dd45a95e3b1"},
+    {file = "llvmlite-0.40.1rc1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3bc15e54522695ef16b5225cb40e89ef7f80d2d37cb0a8ddf3ffe3200fa238ff"},
+    {file = "llvmlite-0.40.1rc1-cp311-cp311-win_amd64.whl", hash = "sha256:957c5f18726362fd2426f39997b9090c88a6a1cb11d4330b50b4946fa0c857a7"},
+    {file = "llvmlite-0.40.1rc1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:38bcca23eb8919279619bebb4db6946f0d3dfedd879dfe9f741041789c83e36b"},
+    {file = "llvmlite-0.40.1rc1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:753359a969f0606c30d3ef38988ae46c65ef2d3bcc7afb4ada0c37a2f4416a68"},
+    {file = "llvmlite-0.40.1rc1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fae6c6b04ec4d83b5bd3437dd4ef7a9e6d4461437e615fa0895ac355709b6f10"},
+    {file = "llvmlite-0.40.1rc1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f095b6c6e94fcb26705614d9da2267c739118f1e97ba6bb3ea5c9fbc77764171"},
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 [[package]]
 name = "pyinstaller-hooks-contrib"
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+version = "2023.8"
 description = "Community maintained hooks for PyInstaller"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [[package]]
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 [[package]]
 name = "pywebview"
-version = "4.2.2"
+version = "4.3.1"
 description = "Build GUI for your Python program with JavaScript, HTML, and CSS"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
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+version = "0.4.6"
+description = "Play and Record Sound with Python"
+optional = false
+python-versions = ">=3.7"
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+[package.dependencies]
+CFFI = ">=1.0"
+
+[package.extras]
+numpy = ["NumPy"]
+
+[[package]]
+name = "soundfile"
+version = "0.12.1"
+description = "An audio library based on libsndfile, CFFI and NumPy"
+optional = false
+python-versions = "*"
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+cffi = ">=1.0"
+
+[package.extras]
+numpy = ["numpy"]
+
 [[package]]
 name = "spacy"
 version = "3.6.1"
@@ -5734,40 +5909,40 @@ files = [
 
 [[package]]
 name = "tiktoken"
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 optional = false
 python-versions = ">=3.8"
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-    {file = "tiktoken-0.4.0.tar.gz", hash = "sha256:59b20a819969735b48161ced9b92f05dc4519c17be4015cfb73b65270a243620"},
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+    {file = "tiktoken-0.3.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a43612b2a09f4787c050163a216bf51123851859e9ab128ad03d2729826cde9"},
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+    {file = "tiktoken-0.3.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:65fc0a449630bab28c30b4adec257442a4706d79cffc2337c1d9df3e91825cdd"},
+    {file = "tiktoken-0.3.3-cp39-cp39-win_amd64.whl", hash = "sha256:0b9a7a9a8b781a50ee9289e85e28771d7e113cc0c656eadfb6fc6d3a106ff9bb"},
+    {file = "tiktoken-0.3.3.tar.gz", hash = "sha256:97b58b7bfda945791ec855e53d166e8ec20c6378942b93851a6c919ddf9d0496"},
 ]
 
 [package.dependencies]
@@ -6214,13 +6389,13 @@ pscript = ">=0.7.0,<0.8.0"
 
 [[package]]
 name = "virtualenv"
-version = "20.24.3"
+version = "20.24.4"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.24.3-py3-none-any.whl", hash = "sha256:95a6e9398b4967fbcb5fef2acec5efaf9aa4972049d9ae41f95e0972a683fd02"},
-    {file = "virtualenv-20.24.3.tar.gz", hash = "sha256:e5c3b4ce817b0b328af041506a2a299418c98747c4b1e68cb7527e74ced23efc"},
+    {file = "virtualenv-20.24.4-py3-none-any.whl", hash = "sha256:29c70bb9b88510f6414ac3e55c8b413a1f96239b6b789ca123437d5e892190cb"},
+    {file = "virtualenv-20.24.4.tar.gz", hash = "sha256:772b05bfda7ed3b8ecd16021ca9716273ad9f4467c801f27e83ac73430246dca"},
 ]
 
 [package.dependencies]
@@ -6229,7 +6404,7 @@ filelock = ">=3.12.2,<4"
 platformdirs = ">=3.9.1,<4"
 
 [package.extras]
-docs = ["furo (>=2023.5.20)", "proselint (>=0.13)", "sphinx (>=7.0.1)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [[package]]
@@ -6558,4 +6733,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "3.10.x"
-content-hash = "89726872f12f1c780732db0531d257e6156b8e0c3aca9865d8ad2dc03ec030e2"
+content-hash = "09f677ee1d0b7bbfb4ce051ece7b85fc84ef43782d0285f0c90cf4321e4ad5df"
diff --git a/pyproject.toml b/pyproject.toml
index e05451d34..1291ba5eb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -45,7 +45,6 @@ rapidocr-onnxruntime = "1.2.3"
 scikit-learn = "1.2.2"
 scipy = "1.9.3"
 sqlalchemy = "1.4.43"
-tiktoken = "0.4.0"
 torch = "^2.0.0"
 tqdm = "4.64.0"
 transformers = "4.29.2"
@@ -86,6 +85,11 @@ click = "^8.1.6"
 spacy-transformers = "^1.2.5"
 boto3 = "^1.28.30"
 botocore = "^1.31.30"
+llvmlite = "0.40.1rc1"
+numba = "0.57.0"
+openai-whisper = {git = "https://github.com/openai/whisper.git"}
+sounddevice = "^0.4.6"
+soundfile = "^0.12.1"
 
 [tool.pytest.ini_options]
 filterwarnings = [