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Ear Training Module for TouchGrass.
Guides ear training exercises without audio, using descriptive language.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import Optional, List, Dict, Tuple
class EarTrainingModule(nn.Module):
"""
Guides ear training exercises without audio.
Can:
- Describe interval sounds in relatable terms
("a perfect 5th sounds like the Star Wars theme opening")
- Generate solfege exercises (Do Re Mi Fa Sol La Ti Do)
- Create interval identification quizzes in text form
- Explain chord quality by ear ("major chords sound happy/bright,
minor chords sound sad/dark, diminished chords sound tense/unstable")
- Guide relative pitch training
- Suggest listening exercises with specific songs/moments
Tracks user progress through session context.
"""
# Intervals (semitones)
INTERVALS = {
0: "unison",
1: "minor 2nd",
2: "major 2nd",
3: "minor 3rd",
4: "major 3rd",
5: "perfect 4th",
6: "tritone",
7: "perfect 5th",
8: "minor 6th",
9: "major 6th",
10: "minor 7th",
11: "major 7th",
12: "octave",
}
# Interval qualities
QUALITIES = ["perfect", "major", "minor", "augmented", "diminished"]
# Solfege syllables (movable do)
SOLFEGE = ["Do", "Re", "Mi", "Fa", "Sol", "La", "Ti", "Do"]
# Chord qualities and descriptions
CHORD_DESCRIPTIONS = {
"major": "bright, happy, stable",
"minor": "sad, dark, melancholic",
"diminished": "tense, unstable, dissonant",
"augmented": "bright, dreamy, suspenseful",
"dominant7": "bluesy, tense, wants to resolve",
"major7": "smooth, jazzy, dreamy",
"minor7": "smooth, soulful, mellow",
}
# Famous song references for intervals
INTERVAL_SONGS = {
0: "any note played twice",
1: "Jaws theme (da-dum)",
2: "Happy Birthday (2nd note)",
3: "When the Saints Go Marching In (minor 3rd)",
4: "Oh When the Saints (major 3rd)",
5: "Here Comes the Bride (perfect 4th)",
6: "The Simpsons theme (tritone)",
7: "Star Wars theme (perfect 5th)",
8: "My Bonnie Lies Over the Ocean (minor 6th)",
9: "Somewhere Over the Rainbow (major 6th)",
10: "The Office theme (minor 7th)",
11: "Take On Me (major 7th)",
12: "Somewhere Over the Rainbow (octave)",
}
def __init__(self, d_model: int):
"""
Initialize EarTrainingModule.
Args:
d_model: Hidden dimension from base model
"""
super().__init__()
self.d_model = d_model
# Embeddings
self.interval_embed = nn.Embedding(13, 64) # unison through octave
self.quality_embed = nn.Embedding(5, 64) # perfect/major/minor/aug/dim
# Difficulty tracker (skill level 1-5)
self.difficulty_tracker = nn.Linear(d_model, 5)
# Exercise type classifier
self.exercise_type_head = nn.Linear(d_model, 6) # 6 exercise types
# Interval prediction head
self.interval_predictor = nn.Linear(d_model, 13)
# Chord quality predictor
self.chord_quality_predictor = nn.Linear(d_model, 7)
# Solfege generator
self.solfege_generator = nn.GRU(
input_size=d_model + 64,
hidden_size=d_model,
num_layers=1,
batch_first=True,
)
# Progress tracker (simple RNN to track session history)
self.progress_tracker = nn.GRU(
input_size=5, # one-hot for exercise types
hidden_size=64,
num_layers=1,
batch_first=True,
)
# Success rate predictor
self.success_predictor = nn.Linear(64, 1)
def forward(
self,
hidden_states: torch.Tensor,
exercise_type: Optional[int] = None,
user_response: Optional[str] = None,
) -> Dict[str, torch.Tensor]:
"""
Forward pass through EarTrainingModule.
Args:
hidden_states: Base model hidden states [batch, seq_len, d_model]
exercise_type: Optional exercise type ID (0-5)
user_response: Optional user's answer for progress tracking
Returns:
Dictionary with ear training predictions
"""
batch_size, seq_len, _ = hidden_states.shape
# Pool hidden states
pooled = hidden_states.mean(dim=1) # [batch, d_model]
# Predict difficulty level
difficulty_logits = self.difficulty_tracker(pooled) # [batch, 5]
# Predict exercise type
exercise_logits = self.exercise_type_head(pooled) # [batch, 6]
# Predict interval
interval_logits = self.interval_predictor(pooled) # [batch, 13]
# Predict chord quality
chord_quality_logits = self.chord_quality_predictor(pooled) # [batch, 7]
outputs = {
"difficulty_logits": difficulty_logits,
"exercise_type_logits": exercise_logits,
"interval_logits": interval_logits,
"chord_quality_logits": chord_quality_logits,
}
return outputs
def describe_interval(self, interval_semitones: int, reference: str = "song") -> str:
"""
Describe an interval in relatable terms.
Args:
interval_semitones: Number of semitones (0-12)
reference: Type of reference ("song", "emotion", "technical")
Returns:
Descriptive string
"""
if interval_semitones not in self.INTERVALS:
return f"Unknown interval: {interval_semitones} semitones"
interval_name = self.INTERVALS[interval_semitones]
if reference == "song":
song = self.INTERVAL_SONGS.get(interval_semitones, "a generic interval")
return f"A {interval_name} ({interval_semitones} semitones) — like {song}."
elif reference == "emotion":
# Map intervals to emotional descriptors
emotion_map = {
0: "familiar, consonant",
1: "tense, dissonant",
2: "slightly tense",
3: "sad, soulful",
4: "bright, happy",
5: "stable, resolved",
6: "very tense, mysterious",
7: "strong, stable",
8: "sweet, melancholic",
9: "bright, hopeful",
10: "bluesy, tense",
11: "smooth, jazzy",
12: "complete, resolved",
}
emotion = emotion_map.get(interval_semitones, "neutral")
return f"A {interval_name} feels {emotion}."
else:
return f"A {interval_name} spans {interval_semitones} semitones."
def generate_solfege_exercise(
self,
key: str = "C",
difficulty: int = 1,
num_notes: int = 5,
) -> List[str]:
"""
Generate solfege exercise.
Args:
key: Key signature (affects accidentals)
difficulty: 1-5, higher = more accidentals, larger jumps
num_notes: Number of notes in exercise
Returns:
List of solfege syllables
"""
import random
# Simple pentatonic scale for low difficulty
if difficulty <= 2:
# Stepwise motion, no accidentals
start_idx = random.randint(0, 4) # Do to Sol
exercise = []
for i in range(num_notes):
idx = (start_idx + i) % 7
exercise.append(self.SOLFEGE[idx])
return exercise
else:
# More complex: wider leaps, accidentals
exercise = []
current = 0 # Start at Do
for _ in range(num_notes):
# Jump size increases with difficulty
max_jump = min(difficulty + 2, 7)
jump = random.randint(-max_jump, max_jump)
current = max(0, min(6, current + jump))
exercise.append(self.SOLFEGE[current])
return exercise
def generate_interval_quiz(
self,
num_questions: int = 5,
max_interval: int = 12,
include_desc: bool = True,
) -> List[Dict]:
"""
Generate interval identification quiz.
Args:
num_questions: Number of questions
max_interval: Maximum interval size (up to 12)
include_desc: Include descriptive hints
Returns:
List of quiz questions
"""
import random
questions = []
for _ in range(num_questions):
interval = random.randint(1, max_interval)
quality = "perfect" if interval in [1, 4, 5, 8, 11, 12] else random.choice(["major", "minor"])
question = {
"interval_semitones": interval,
"interval_name": self.INTERVALS[interval],
"quality": quality,
}
if include_desc:
question["hint"] = self.describe_interval(interval, reference="song")
questions.append(question)
return questions
def describe_chord_quality(self, chord_type: str) -> str:
"""
Describe how a chord quality sounds.
Args:
chord_type: Chord type (major, minor, etc)
Returns:
Descriptive string
"""
description = self.CHORD_DESCRIPTIONS.get(chord_type, "unique sounding")
return f"{chord_type} chords sound {description}."
def suggest_listening_exercise(
self,
interval: Optional[int] = None,
chord_quality: Optional[str] = None,
) -> Dict[str, str]:
"""
Suggest specific songs/moments to listen for intervals or chords.
Args:
interval: Optional specific interval to practice
chord_quality: Optional chord quality to practice
Returns:
Dictionary with listening suggestions
"""
suggestions = {}
if interval:
song = self.INTERVAL_SONGS.get(interval, "various songs")
suggestions["interval"] = f"Listen for {self.INTERVALS[interval]} in: {song}"
suggestions["tip"] = "Try to hum along to internalize the sound."
if chord_quality:
# Provide famous examples
examples = {
"major": ["Happy Birthday", "Let It Be (chorus)"],
"minor": ["House of the Rising Sun", "Greensleeves"],
"diminished": ["The Simpsons theme (tritone)"],
"dominant7": ["Blues progressions", "Purple Haze"],
"major7": ["Something (The Beatles)", "So What (Miles Davis)"],
}
songs = examples.get(chord_quality, ["various songs"])
suggestions["chord"] = f"Listen for {chord_quality} chords in: {', '.join(songs)}"
suggestions["tip"] = "Focus on the emotional character."
return suggestions
def track_progress(
self,
exercise_history: List[Dict],
current_performance: float,
) -> Dict[str, any]:
"""
Track user's progress over session.
Args:
exercise_history: List of past exercises with scores
current_performance: Current success rate (0-1)
Returns:
Progress analysis
"""
if not exercise_history:
return {"level": "beginner", "suggestion": "Start with interval identification"}
# Calculate average performance
avg_performance = sum(ex.get("score", 0) for ex in exercise_history) / len(exercise_history)
# Determine level
if avg_performance < 0.5:
level = "beginner"
suggestion = "Practice more interval identification with smaller intervals (2nd-5th)."
elif avg_performance < 0.7:
level = "intermediate"
suggestion = "Try more complex intervals and chord qualities."
else:
level = "advanced"
suggestion = "Challenge yourself with inversions and advanced chords."
return {
"level": level,
"average_score": avg_performance,
"current_score": current_performance,
"suggestion": suggestion,
"exercises_completed": len(exercise_history),
}
def test_ear_training_module():
"""Test the EarTrainingModule."""
import torch
# Create module
module = EarTrainingModule(d_model=4096)
# Test input
batch_size = 2
seq_len = 10
d_model = 4096
hidden_states = torch.randn(batch_size, seq_len, d_model)
# Forward pass
outputs = module.forward(hidden_states)
print("Ear Training Module outputs:")
for key, value in outputs.items():
print(f" {key}: {value.shape}")
# Test interval description
print("\nInterval descriptions:")
for semitones in [3, 4, 5, 7, 10]:
desc = module.describe_interval(semitones, reference="song")
print(f" {semitones} semitones: {desc}")
# Test solfege exercise
print("\nSolfege exercise (C, difficulty 2):")
solfege = module.generate_solfege_exercise(key="C", difficulty=2, num_notes=8)
print(f" {' '.join(solfege)}")
# Test interval quiz
print("\nInterval quiz (3 questions):")
quiz = module.generate_interval_quiz(num_questions=3)
for i, q in enumerate(quiz):
print(f" Q{i+1}: {q['interval_name']} ({q['interval_semitones']} semitones)")
if 'hint' in q:
print(f" Hint: {q['hint']}")
# Test chord description
print("\nChord quality descriptions:")
for chord in ["major", "minor", "diminished", "major7"]:
desc = module.describe_chord_quality(chord)
print(f" {chord}: {desc}")
# Test listening suggestions
print("\nListening exercise suggestions:")
suggestions = module.suggest_listening_exercise(interval=7, chord_quality="major")
for key, value in suggestions.items():
print(f" {key}: {value}")
# Test progress tracking
print("\nProgress tracking:")
history = [
{"exercise": "interval", "score": 0.6},
{"exercise": "interval", "score": 0.7},
{"exercise": "chord", "score": 0.5},
]
progress = module.track_progress(history, current_performance=0.8)
for key, value in progress.items():
print(f" {key}: {value}")
print("\nEar Training Module test complete!")
if __name__ == "__main__":
test_ear_training_module() |