Lesson 2 Teaching Plan (ICT)

Lesson Title

Offline Speech Recognition & Synthesis + Python Basics (Data Types, Input, Comments)

Duration

80 minutes

Learning Objectives

Use whisper for offline speech recognition and pyttsx3 for offline speech synthesis.
Understand and use different data types in Python (strings, integers, floats, booleans).
Use input() to get information from the user.
Write comments to explain and document code.

Teaching Materials

Software

PyCharm (pre‑installed)
Python 3.8 or higher (pre‑installed)
Libraries: whisper, pyttsx3, speech_recognition (pre‑installed)

Hardware

Teacher’s computer with projector and speakers
Student computers (one per student/pair)
Microphones (built‑in or external)
Headphones or speakers for audio output

Additional Resources

Student Handbook (Lesson 2 section, printed or digital)
Pre‑downloaded Whisper model (small)

Teaching Process

Segment 1 (30 minutes) – Content Delivering

1. Lesson 1 Recap & Lesson 2 Introduction (3 minutes)

Lesson 1: online TTS (edge_tts) + offline recognition (whisper).
Today: both synthesis and recognition work offline.
New Python topics: data types, input(), comments.

Quick recap questions:

What does import do? (Brings tools into Python)
How do you identify a function? (It has parentheses ())
What is a parameter? (Information inside the parentheses)

2. Python Concept 1: Comments

# This is a comment — Python ignores this line
print("Hello")  # This comment explains what print does

Purpose: for humans only, explains code.
Use in homework and projects.

3. Python Concept 2: Data Types (7 minutes)

# String (text, inside quotes)
name = "Alice"
message = 'Hello'

# Integer (whole number, no decimal)
age = 12
score = -5

# Float (decimal number)
height = 1.55
price = 19.99

# Boolean (True or False)
is_student = True
like_python = False

Data Type	What it stores	Example
String	Text	`"Python"`
Integer	Whole numbers	`12`, `-5`
Float	Decimal numbers	`1.55`, `3.14`
Boolean	True or False	`True`, `False`

4. Python Concept 3:

# input() asks the user to type something
name = input("What is your name? ")
print("Hello, " + name)

# input() always returns a STRING
age_input = input("How old are you? ")
age_number = int(age_input)  # convert string to integer
next_age = age_number + 1

print("Next year you will be", next_age)

Key point: input() → string; use int()/float() for numbers.

5. New Libraries:

Library	Purpose	Online/Offline
`whisper`	Speech recognition	Offline
`pyttsx3`	Text‑to‑speech synthesis	Offline

Both work without internet, private and portable.

6. Code Walkthrough – Offline Speech Recognition (

import whisper
import speech_recognition as sr

# Load whisper model
model = whisper.load_model("small")

# Record from microphone
recognizer = sr.Recognizer()
with sr.Microphone() as source:
    print("Please speak...")
    audio = recognizer.listen(source)

# Save temporary audio file
with open("temp.wav", "wb") as f:
    f.write(audio.get_wav_data())

# Offline recognition
result = model.transcribe("temp.wav")
print("You said:", result["text"])

7. Code Walkthrough – Offline Speech Synthesis (

import pyttsx3

# Initialize TTS engine
engine = pyttsx3.init()

# Optional settings
engine.setProperty('rate', 150)     # speed
engine.setProperty('volume', 0.9)   # volume

# Speak text
engine.say("Hello, I am your offline voice assistant.")
engine.say("I don't need internet to work.")

engine.runAndWait()

Segment 2 (50 minutes) – Practice & Differentiated Tasks

Task 1: Data Types Practice (8 minutes)

File: task1_datatypes.py

# String
my_name = "Your Name"
print("My name is:", my_name)

# Integer
my_age = 12
print("My age is:", my_age)

# Float
my_height = 1.55
print("My height is:", my_height)

# Boolean
like_python = True
print("I like Python:", like_python)

Change values to your own.
Add a comment above each variable.

Task 2:

File: task2_input.py

# Ask for name
name = input("What is your name? ")
print("Nice to meet you, " + name + "!")

# Ask for favourite subject
subject = input("What is your favourite subject? ")
print(subject + " is a great subject!")

# Ask for a number and do maths
number = input("Choose a number: ")
number_int = int(number)
print("Your number plus 10 is", number_int + 10)

Task 3: Offline Speech Synthesis (

File: task3_speak.py

import pyttsx3

# Initialize the TTS engine
engine = pyttsx3.init()

# Change speed and volume
engine.setProperty('rate', 150)
engine.setProperty('volume', 0.9)

# Speak sentences
engine.say("Hello! I am your offline voice assistant.")
engine.say("I can speak without internet connection.")
engine.say("This is lesson two of our Python course.")

engine.runAndWait()

Change the sentences.
Try different rate and volume values.

Task 4: Offline Speech Recognition (

File: task4_listen.py

import whisper
import speech_recognition as sr

print("Loading whisper model...")
model = whisper.load_model("small")
print("Model loaded!")

# Record
recognizer = sr.Recognizer()
with sr.Microphone() as source:
    print("Please speak a sentence...")
    audio = recognizer.listen(source)

# Save temp file
with open("temp.wav", "wb") as f:
    f.write(audio.get_wav_data())

# Recognize
print("Recognising...")
result = model.transcribe("temp.wav")
print("You said:", result["text"])

print("Characters:", len(result["text"]))

Task 5: Combine

File: task5_echo.py

import pyttsx3

engine = pyttsx3.init()

user_text = input("What should I say? ")

engine.say(user_text)
engine.runAndWait()

print("Done speaking!")

Teaching Evaluation

Learning Objective	Evaluation Method
Offline recognition with `whisper`	Completion of Task 4
Offline synthesis with `pyttsx3`	Completion of Task 3
Understand and use data types	Task 1: correct variable types
Use `input()`	Task 2: program asks and responds
Write comments	All tasks include meaningful comments

Offline AI Model