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Read more about the article How to organise a successful Google Code-In meetup

How to organise a successful Google Code-In meetup

In this blog post I hope to write about what is Google Code-In and the best way to organise a successful Google Code-In meetup or workshop in your local community. I hope you will find everything that you need to know about conducting a successful meetup. What is Google Code-In ? Google Code-In is a global and an open source contest funded by Google to give real world software development experience to pre-university students who are in age range 13-17. Beside of software developing, this contest’s main objective is to motivate tech enthusiastic students to contribute to opensource and give them the knowledge about open source software development. The usual timeline of the contest is, it opens for students on end of the November and runs until mid of January. There are 25 open source organizations participating for Google Code-In this time. Your role ? As a GCI mentor , past GCI student or an open source contributor you have a responsibility towards the community. That is to expand the community awareness and transfer your knowledge to next generation. You gather experience while working on the open source projects and GCI is the best place to give your knowledge to youngsters while working with them. You should be devoted to guide students and give them an introduction to open source software development. How students can be a part of the contest ? Any pre-university student in age group 13-17 can register for the contest. The following four steps needs to be followed by the student to be eligible to compete in the contest. Sign up at g.co/gci after reading the Contest Rules. Ask their parent or legal guardian to sign the Parental Consent form. Find a task that interests them. Claim the task and start working while getting guidance from the mentors. In return to their hard work and open source contribution, students can win digital certificates, t-shirts, hoodies based on their performance as well as a trip to Google HeadQuarters for Grand Prize Winner. How to organize a local meetup ? Since the Google Code-In contest is for pre-university students, I highly recommend that you organize a meetup for schools in the community. You can easily contact the club or society of the school which is related to Information and Communication Technology and convey your idea of the meetup so that the responsible person can get the management approval from their side to facilitate your meetup inside the school. If you are not confident enough to conduct a session on your own maybe because this is a new experience to you, Don’t worry ! You can always call some other past GCI students, GCI mentors or open source contributors to collaborate with you in conducting a successful session. As open source world teaches us, it’s always collaboration that brings success to any project. Taking the start to the meetup, you need to give an introduction to the Google Code-In. You may find different questions from the audience about “What…

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Read more about the article Adding IBM Watson TTS Support in Susi Assistant on Raspberry Pi

Adding IBM Watson TTS Support in Susi Assistant on Raspberry Pi

Susi Hardware project aims at creating a smart assistant for your home that you can run on your Raspberry Pi or similar Development Boards. I previously wrote a blog on choosing a perfect Text to Speech engine for Susi AI and had used Flite as the solution for it. While Flite is an Open Source solution that can run locally on a client, it does not provide the same quality of voice and speed as cloud providers. We always crave for a more natural voice for better interaction with our assistant. It is always good to have more options. We, therefore, added IBM Watson Text to Speech API in SUSI Hardware project. IBM Watson TTS can be added to a Python Project easily using the IBM Watson Developer SDK. For using the IBM Watson Developer SDK for Text to Speech, first of all, we need to sign up for Bluemix https://console.bluemix.net/registration/ After that, we will get the empty dashboard without any service added currently. We need to create a Text to Speech Service. To do so, click on Create Watson Service button      Select Watson on the left pane and then select Text to Speech service from the list. Select the standard plan from the options and then click on create button. You will get service credentials for your newly created text to speech service. Save it for future reference. After that, we need to add Watson developer cloud python package. sudo pip3 install watson-developer-cloud On Ubuntu with Python 3.5 watson-developer-cloud has some extra dependencies. Install them using the following command. sudo apt install libssl-dev Now we can add Text to Speech to our project. For that, we need to first import TextToSpeechV1 library. It can be added using following import statement. from watson_developer_cloud import TextToSpeechV1 Now we need to create a new TextToSpeechV1 object using the Service Credentials we created earlier. text_to_speech = TextToSpeechV1( username='API_USERNAME', password='API_PASSWORD') We can now perform synthesis of a text input and write the incoming speech stream from IBM Watson API to a file. with open('output.wav', 'wb') as audio_file: audio_file.write( text_to_speech.synthesize(text, accept='audio/wav’, voice='en-US_AllisonVoice')) In the above code snippet,  we are opening an output file ‘output.wav’ for writing. We then write the binary audio data returned by text_to_speech.synthesize method. IBM Watson provides many free voices. We supply an argument specifying which voice we need to use. We are using English female ‘en-US_AllisonVoice’. You may test out more voices in the online demo here and select the voice that you find best. We can play the ‘output.wav’ file using the play command from SoX. To do so, we need to install SoX binary. sudo apt install sox libsox-fmt-all We can play the file easily now using the following code. import os os.system('play output.wav') The above code invokes the ‘play’ command from the SoX package to play the audio file. We can also use PyAudio to play the audio file but it would require us to manage the audio thread separately. Thus, SoX is a better solution. Resources:…

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Read more about the article Setup SUSI Assistant on Raspberry Pi in under 30 minutes

Setup SUSI Assistant on Raspberry Pi in under 30 minutes

With our ever growing list of list of platforms supported by Susi AI, we now have a client that can run on Raspberry Pi and you can access it hands-free!! Here is a video that you can refer for its working. https://youtu.be/au0MAc0GF6w But it might have left you wondering how you can replicate such a setup yourself? It is fairly easy and will be done fairly easy. Just follow the following instructions. You need to have following hardware in order to have your own SUSI Assistant running on Raspberry Pi. A Raspberry Pi (prefer 2 or 3) with Raspbian Jessie OS. A stable internet connection.  ( Recommended 4 Mbps ) A USB Microphone /  USB Webcam with Microphone. You may buy one like this. A Speaker that connects through 3.5mm jack. You may buy one like this. After you get all the above items in order, you need to get access to a terminal of your Raspberry Pi. You can have that by either connecting a monitor to Raspberry Pi temporarily or by connecting to Raspberry Pi over SSH. Once this is done, next step is the installation of the dependencies. The installation of the SUSI on Raspberry is automated after dependencies are installed. Run the following command on Raspberry Pi terminal. sudo apt install git swig3.0 portaudio19-dev pulseaudio libpulse-dev unzip sox libatlas-dev libatlas-base-dev libsox-fmt-all python3 After this, you may check if your output and input devices are working alright. For this, run rec recording.wav . It will start recording audio and saving it to a file named recording.wav. Play back the file using play recording.wav If you hear your audio clearly, setup is done right else you need to configure your Audio Devices correctly.  Most of the time the configuration of Audio works out the box and devices are plug and play so you would not encounter any errors. If you are successful in configuring your devices, install extra dependencies for SUSI Hardware by running the automated install script. In your terminal run, $ git clone https://github.com/fossasia/susi_hardware.git $ cd susi_hardware $ ./install.sh This will install all the remaining dependencies. After the above step is complete, you may run configuration file generator script to choose the Text to Speech and Speech to Text service according to your wish. For doing so, you need to run $ python3 config_generator.py Follow the instructions in the script. It will ask you to configure the default service for Text to Speech and Speech to Text and other options. After the configuration is complete, you can simply run the following command to start SUSI. $ python3 main.py This will start SUSI in a continuously listening mode. You may invoke SUSI anytime, just by saying SUSI followed by a query. The query will be answered by SUSI subsequently. Since configurations for different hardware devices may vary, you may encounter some problems. In such a scenario, you may refer to the following resources to solve the issues. Resources: For Setting up Audio properly: - Debian Pulseaudio setup guide. For setting up…

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