diff --git a/.github/workflows/python-demo.yml b/.github/workflows/python-demo.yml
index e35f1155..f14c2bb8 100644
--- a/.github/workflows/python-demo.yml
+++ b/.github/workflows/python-demo.yml
@@ -62,7 +62,7 @@ jobs:
         run: >
           python3 orca_demo_streaming.py
           --access_key ${{secrets.PV_VALID_ACCESS_KEY}}
-          --text "Hello, I am Orca!"
+          --text_to_stream "Hello, I am Orca!"
 
       - name: Test single
         run: >
@@ -97,7 +97,7 @@ jobs:
         run: >
           python3 orca_demo_streaming.py
           --access_key ${{secrets.PV_VALID_ACCESS_KEY}}
-          --text "Hello, I am Orca!"
+          --text_to_stream "Hello, I am Orca!"
 
       - name: Test single
         run: >
diff --git a/README.md b/README.md
index 59b3153e..464685bf 100644
--- a/README.md
+++ b/README.md
@@ -69,9 +69,6 @@ This enables seamless conversations with voice assistants, eliminating any audio
 
 ![](https://github.com/Picovoice/orca/blob/orca-prepare-v0.2/resources/assets/orca_streaming_animation.gif)
 
-As demonstrated above, Orca starts converting text to audio right away, while other TTS systems, such as OpenAI TTS,
-need to wait for the entire LLM output to be available, introducing a delay in the voice assistant's response.
-
 Orca also supports single synthesis mode, where a complete text is synthesized in a single call to the Orca engine.
 
 ### Text input
@@ -133,16 +130,20 @@ AccessKey also verifies that your usage is within the limits of your account. Ev
 
 ### Python Demos
 
-To run the Python demo, run the following in the console:
+Install the demo package:
 
 ```console
 pip3 install pvorcademo
 ```
 
+Run the streaming demo:
+
 ```console
-orca_demo_streaming --access_key ${ACCESS_KEY} --text-to-stream ${TEXT}
+orca_demo_streaming --access_key ${ACCESS_KEY} --text_to_stream ${TEXT}
 ```
 
+Run the single synthesis demo:
+
 ```console
 orca_demo --access_key ${ACCESS_KEY} --text ${TEXT} --output_path ${WAV_OUTPUT_PATH}
 ```
@@ -150,6 +151,8 @@ orca_demo --access_key ${ACCESS_KEY} --text ${TEXT} --output_path ${WAV_OUTPUT_P
 Replace `${ACCESS_KEY}` with yours obtained from Picovoice Console, `${TEXT}` with the text to be synthesized, and
 `${WAV_OUTPUT_PATH}` with a path to an output WAV file.
 
+For more information about Python demos go to [demo/python](demo/python).
+
 ### iOS Demo
 
 Run the following from [demo/ios](demo/ios) to install the Orca-iOS CocoaPod:
diff --git a/demo/python/README.md b/demo/python/README.md
index 3ffd1582..f8d11e8d 100644
--- a/demo/python/README.md
+++ b/demo/python/README.md
@@ -48,7 +48,7 @@ We stream that text to Orca and play the synthesized audio as soon as it gets ge
 To run it, execute the following:
 
 ```console
-orca_demo_streaming --access_key ${ACCESS_KEY} --text-to-stream ${TEXT}
+orca_demo_streaming --access_key ${ACCESS_KEY} --text_to_stream ${TEXT}
 ```
 
 Replace `${ACCESS_KEY}` with your `AccessKey` obtained from Picovoice Console and `${TEXT}` with your text to be
diff --git a/demo/python/orca_demo_streaming.py b/demo/python/orca_demo_streaming.py
index f559ea5f..05b0d92e 100644
--- a/demo/python/orca_demo_streaming.py
+++ b/demo/python/orca_demo_streaming.py
@@ -300,22 +300,22 @@ def main() -> None:
         "-m",
         help="Absolute path to Orca model. Default: using the model provided by `pvorca`")
     parser.add_argument(
-        "--text-to-stream",
+        "--text_to_stream",
         "-t",
         required=True,
         help="Text to be streamed to Orca")
     parser.add_argument(
-        "--tokens-per-second",
+        "--tokens_per_second",
         type=int,
         default=15,
         help="Number of tokens per second to be streamed to Orca, simulating an LLM response.")
     parser.add_argument(
-        "--audio-wait-chunks",
+        "--audio_wait_chunks",
         type=int,
         default=None,
         help="Number of PCM chunks to wait before starting to play audio. Default: system-dependent.")
     parser.add_argument(
-        "--show-audio-devices",
+        "--show_audio_devices",
         action="store_true",
         help="Only list available audio output devices and exit")
     parser.add_argument('--audio-device-index', type=int, default=None, help='Index of input audio device')