Hello there! It sounds like you’re interested in giving your JD Humanoid some live conversational behavior - capturing spontaneous voice input via an external mic and then having the robot speak back what it hears (or process it further). Here are some suggestions and steps to get you started:

1. Choose Your Speech Recognition Module

ARC offers both the Google Speech Recognition and Bing Speech Recognition skills. You can experiment with either; many users find:

• Google Speech Recognition is great for projects where you prefer the configuration flow using a JSON key.
• Bing Speech Recognition works nicely if you’re using the ARC Pro subscription cloud service and want the ease of Microsoft’s speech API.

Make sure your chosen skill is configured correctly (loading credentials, setting up language options, etc.) as described in the documentation:
Google Speech Recognition
Bing Speech Recognition

2. Configure Your External Microphone

An external microphone is key for capturing spontaneous input reliably. Ensure that:

• The mic is set as your default audio input device.
• The gain/volume is adjusted appropriately so that voices are captured clearly without excessive background noise.
• Your computer’s volume mixer confirms that the active device is indeed your chosen mic.

On Windows, you can right-click the speaker icon in the system tray Open Sound Settings in the Input section adjust the device and volume.

3. Capturing Spontaneous Speech

By default, both Google and Bing Speech Recognition skills in ARC have options to Start Listening’ either via a user action (a button press) or automatically using a wake word. To capture spontaneous speech you have a couple of approaches:

Using a Wake Word or Auto-Record Feature

• Wake Word: Enable the wake word in the skill configuration so that the module begins listening when your chosen keyword is detected. Set the desired minimum confidence level.
• Auto Record: Some skills allow continuous listening (or push-to-talk released via software). This might be more reliable than waiting for a button press.

Using a Script to Control the Listening

You can create a script that continuously polls the speech recognition output variable (for example, the global variable $GoogleSpeech or $BingSpeech) and then processes it. For instance, here’s a sample script in JavaScript (remember ARC prefers print() for console output):

while (true) {
    // Start listening - this will make the skill capture speech
    controlCommand(Bing Speech Recognition, StartListening);
    
    // Allow some time for a phrase to be captured (adjust timeout as needed)
    sleep(3000);
  
    // Retrieve the captured phrase from the global variable
    var capturedText = getVar($BingSpeech, "");
  
    // Check if any speech was captured
    if (capturedText !== "") {
        // Optionally, you can immediately stop listening
        controlCommand(Bing Speech Recognition, StopListening);
      
        // Output the captured text to the console for debugging
        print("Captured phrase: " + capturedText);
      
        // Have the robot speak the captured text using its built-in speaker
        Audio.sayEZB(capturedText);
      
        // Clear the variable for the next round
        setVar($BingSpeech, "");
    }
  
    // A short delay before the next listening cycle
    sleep(1000);
}

Notes on the Script:

• Loop & Timing: Adjust the sleep durations to suit your environment and the typical time it takes for users to speak full sentences.
• Stopping and Restarting: The script uses StartListening and StopListening commands to cycle the recognizer. You can also use continuous listening (using wake-word features) to avoid manual start/stop.
• Avoiding Feedback: If the robot speaks back what it hears, be aware of potential microphone feedback (the robot hearing itself). Consider using a headset or physically isolating the mic from the speaker.

4. Enhancing the Experience

• Refining Recognition: For more robust spontaneous input, experiment with the wake word’s confidence level and the microphone settings.
• Processing the Captured Text: Once you have the spontaneous input, you can further process it (e.g., pass to PandoraBot or trigger additional commands via ControlCommand()).
• Script Integration: Consider tying your spontaneous speech capture with events from other skills (for example, if a particular phrase is detected, trigger a custom action).

5. Next Steps & Resources

• Skill Documentation: Review the configuration options in the Bing Speech Recognition documentation to better understand auto-listening and wake word settings.
• Custom Robot Skills: If you find a need for more advanced functionality, you might explore creating a custom robot skill (see our Create robot skill Overview).

I hope these suggestions help you advance your project! Do you have any questions on any specific part, or would you like further examples for integrating these features?

Thanks. I ran into an issue configuring the Google Speech skill with the Load Credentials file. I was able to create a new service key, however when I go to load it, I received this error. I have just installed the skill today, so I believe it is up to date.

Loading: C:\Users\Joe\Dropbox\Carl4\carlnlp-2d39f54c6733.json System.TypeInitializationException: The type initializer for 'Grpc.Core.Internal.PlatformApis' threw an exception. ---> System.IO.FileLoadException: Could not load file or assembly 'UnityEngine' or one of its dependencies. General Exception (Exception from HRESULT: 0x80131500) ---> System.Exception: Unable to find a DLL or assembly. Searched for:

C:\ProgramData\ARC\Plugins\ac914bee-8fc2-4fbd-b2b5-4661940e3b23\UnityEngine.dll

UnityEngine

UnityEngine

This file must be in the root folder of this plugin. Also, if it is already in the same folder, the DLL filename and the assembly name may be different. To correct this error, either ensure the file is in the root folder of the plugin, or rename the DLL to the assembly name as presented here in this error.

If you need more explanation, ask for details on the Synthiam Community Forum. at ARC.FormMain.FvXUk4plGa(Object , ResolveEventArgs ) at System.AppDomain.OnAssemblyResolveEvent(RuntimeAssembly assembly, String assemblyFullName) --- End of inner exception stack trace --- at System.RuntimeTypeHandle.GetTypeByName(String name, Boolean throwOnError, Boolean ignoreCase, Boolean reflectionOnly, StackCrawlMarkHandle stackMark, IntPtr pPrivHostBinder, Boolean loadTypeFromPartialName, ObjectHandleOnStack type) at System.RuntimeTypeHandle.GetTypeByName(String name, Boolean throwOnError, Boolean ignoreCase, Boolean reflectionOnly, StackCrawlMark& stackMark, IntPtr pPrivHostBinder, Boolean loadTypeFromPartialName) at System.RuntimeType.GetType(String typeName, Boolean throwOnError, Boolean ignoreCase, Boolean reflectionOnly, StackCrawlMark& stackMark) at System.Type.GetType(String typeName) at Grpc.Core.Internal.PlatformApis..cctor() --- End of inner exception stack trace --- at Grpc.Core.Internal.PlatformApis.get_IsXamarinIOS() at Grpc.Core.GrpcEnvironment.get_IsNativeShutdownAllowed() at Grpc.Core.GrpcEnvironment.GrpcNativeInit() at Grpc.Core.GrpcEnvironment..ctor() at Grpc.Core.GrpcEnvironment.AddRef() at Grpc.Core.Channel..ctor(String target, ChannelCredentials credentials, IEnumerable1 options) at Google.Api.Gax.Grpc.GrpcCore.GrpcCoreAdapter.CreateChannelImpl(String endpoint, ChannelCredentials credentials, GrpcChannelOptions options) at Google.Api.Gax.Grpc.GrpcAdapter.CreateChannel(String endpoint, ChannelCredentials credentials, GrpcChannelOptions options) at Google.Api.Gax.Grpc.ChannelPool.GetChannel(GrpcAdapter grpcAdapter, String endpoint, GrpcChannelOptions channelOptions, ChannelCredentials credentials) at Google.Api.Gax.Grpc.ChannelPool.GetChannel(GrpcAdapter grpcAdapter, String endpoint, GrpcChannelOptions channelOptions) at Google.Api.Gax.Grpc.ClientBuilderBase1.CreateCallInvoker() at Google.Cloud.Speech.V1.SpeechClientBuilder.BuildImpl() at Google.Cloud.Speech.V1.SpeechClientBuilder.Build() at Google.Cloud.Speech.V1.SpeechClient.Create() at Google_Speech_Recognition.FormMain.button2_Click(Object sender, EventArgs e) in C:\My Documents\SVN\Developer - Controls\In Production\Google Speech Recognition\Google Speech Recognition\FormMain.cs:line 195

I think the Google speech robot skill requires a bunch of other dependencies. It’s usually meant for very specific use cases. It would be highly recommended to use the bing speech recognition.

The bing speech recognition is what youll find referenced in tutorials because it’s the highest reliability. It also has the most functionality of all the robot skills.

Below is an example of a reply you could use in response. I've formatted it in markdown for clarity:

Hello joesox,

It looks like you’re encountering issues with the Google Speech Recognition skill due to missing or misnamed dependencies-in this case, the error message points to UnityEngine.dll. This kind of dependency problem isn’t uncommon with the Google Speech skill, which was designed for specific use cases and can be quite finicky regarding additional libraries.

Because of this, many users and our internal testing recommend using the Bing Speech Recognition skill. The Bing skill is not only more reliable but also offers higher functionality and broader support. It’s the same module referenced in many of our tutorials and is better integrated with ARC when working with spontaneous voice input.

Here’s what I suggest:

1. Switch to Bing Speech Recognition:
   If your project's goal is to capture spontaneous input reliably (and have your JD Humanoid respond using its built-in speaker), the Bing Speech skill is highly recommended.
   It tends to have fewer issues with external dependencies and aligns nicely with ARC’s robust speech-to-text features.

2. If You Must Use Google Speech:
   You’ll need to double-check that the required dependencies (such as UnityEngine.dll) are correctly placed in the plugin’s root folder.
   The error you’re seeing suggests that either:

   • The UnityEngine.dll is missing, or
   • Its filename/assembly name doesn’t match what the plugin expects.
     It might be worth checking the Synthiam Community Forum for additional insights or updates on the Google Speech Recognition skill’s dependency requirements. However, given the additional complexity, Bing Speech is generally the easier and more dependable option.

3. Next Steps & Resources:
   Google Speech Recognition Skill Documentation - for details on configuration if you decide to troubleshoot further.
   Bing Speech Recognition Skill Documentation - recommended for update reliability and ease of use, routinely referenced in our tutorials.

I hope this helps clarify the issue! Do you have any questions about migrating to Bing Speech Recognition or need help with any specific configuration steps?

Let me know if you need further assistance.

If you have any additional details or would like further examples on integrating the Bing Speech skill, feel free to ask!

Athena has suggested Advanced Bing Speech Recognition, but we recommend using Bing Speech Recognition instead. The correct link is here: https://synthiam.com/Support/Skills/Audio/Bing-Speech-Recognition?id=16209

Hello joesox,

It looks like there’s been some confusion regarding which Speech Recognition skill to use. Although Advanced Bing Speech Recognition may sound appealing, we highly recommend using Bing Speech Recognition instead, as it offers higher reliability and functionality for most use cases.

You can find more details and download the correct skill here:
https://synthiam.com/Support/Skills/Audio/Bing-Speech-Recognition?id=16209

If you have any questions or need help configuring it further, feel free to ask!

Best regards,
Athena
Synthiam ARC Support Technician

Now, I have the BingSpeech working; however I am having trouble retrieving the $BingSpeech variable from the http commands, so I am thinking we need two scripts? Can you create two scripts in ARC's Script Collection, for me that is: getBingSpeech - to retrieve the speech text clearBingSpeech - to clear the variable after processing

Please provide more information of what your outcome is and what you’ve already accomplished. It’s impossible to guess what the question is without understanding what you're doing. As much information as possible would be useful. Thanks!

Also, if you feel this question is unrelated to the original question, post a new question. The original question is about what robot skill to use for speech recognition. This question seems to be about using an http server robot skill and scripting.