Reimagining Speech and Language Systems: An AI Perspective
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Chapter 1: The Significance of Language
While various species communicate, humans uniquely rely on speech and language as foundational elements of our societal structure and achievements. Through language, we store knowledge and express consciousness, often in the form of internal dialogues. Today, we will examine these communication systems from a broader perspective, noting that while AI is progressing towards replicating these processes, significant challenges remain.
According to Donella Meadows, a pioneer in systems thinking, understanding a complex system begins with examining its outputs. If we were to view humanity as an outsider, we would observe that we produce sounds that convey specific meanings when received by others. Thus, an initial exploration of the speech and language system reveals two primary subsystems: speech production and speech reception, collectively referred to as the dual-stream model. Each subsystem comprises various additional components that interact with major systems like memory and attention. This intricacy calls for a systematic approach to untangle the complexities involved.
Chapter 1.1: Understanding Sound Waves
To grasp the essence of speech, we must first understand sound and its initial reception. The journey begins at the ear, where sound waves are processed. For further insights, you might explore prior discussions on topics such as "Hearing for Robots and AI" and "The Early Consciousness of Sound Through Artificial Counterparts."
Moving forward, when sound waves reach us—let's consider the word "elephant," which typically lasts 1-2 seconds and contains 2-6 syllables—we experience a series of encoding processes. The auditory system first encodes sound as a frequency stream, which then travels to the Auditory Cortex. The subsequent steps remain somewhat mysterious, although it's believed that a hierarchy of pattern detectors operates similarly to those in visual processing, facilitating the extraction of patterns at the phoneme, syllable, and word levels before we can derive meaning.
Chapter 1.2: The Mechanics of Speech Reception
On the left side of the graphic, you will find audio waveforms and spectrograms illustrating sound representations. When visualized, these spectrograms resemble how the brain digitally encodes sounds, with each row corresponding to hair receptor rows in the ear. To the right, this activity is decoded through pattern detectors that recognize phonemes, syllables, and words, forming a rudimentary neural network that activates specific neurons only when the corresponding syllable and pattern detectors are engaged.
Once a word is successfully encoded, we can extract meaning. Current models suggest that meaning is stored in a distributed manner across various modalities, linked by a hub-and-spoke arrangement for generalization. Notably, our understanding of concepts often stems from sensory experiences, even for abstract ideas. For instance, the mental representation of an elephant encompasses its color, shape, and sounds, shaped by personal experiences. Those who have touched an elephant may use their tactile memory to form a definition, while others rely on analogous features they've encountered elsewhere.
Chapter 2: The Process of Speech Production
Speech production can be viewed as the reverse of speech reception. The brain efficiently repurposes many of the reception systems, engaging in a two-step process: first determining what to say (lexical selection) and then figuring out how to articulate it (form encoding). Ultimately, speaking involves coordinating approximately 80 muscles responsible for respiration and vocal modulation to produce meaningful sounds.
To frame the system, the average English vocabulary consists of around 40,000 words, with approximately 15,000 syllables and just 44 phonemes. While this may seem straightforward in dictionary terms, it becomes significantly more complex when considering interconnected networks and their functionalities.
Chapter 2.1: Additional Speech Systems
While our previous discussion focused on word-level interactions, it's essential to recognize that human communication extends to sentences and paragraphs. This involves the prefrontal cortex, short-term memory, and the integration of the two streams, resulting in new cognitive functions, including inner speech.
For instance, learning a new word in a foreign language often entails mimicking spoken or written forms until proficiency is achieved. Over time, we developed a temporary verbal memory store known as the phonological loop, which enables us to retain auditory fragments of speech and repeat them, facilitating their transformation into long-term memories.
Chapter 3: Insights and Implications for AI
AI has made significant strides in speech processing since the 1990s, with systems capable of simulating human conversation. However, challenges remain, including the lack of deep understanding of context and meaning, as AI does not possess the same experiential framework as humans. While current AI can mimic emotional prosody, it lacks a genuine emotional foundation.
In conclusion, speech and language systems consist of two main streams—comprehension and production—intertwined with emotional and memory systems. New functions such as speech rehearsal and covert speech emerge from the intersection of these systems. As we explore AI's current capabilities, it's clear that while some elements of speech and language have been superficially replicated, a deeper understanding and more intricate systems are necessary for more human-like behavior.
I hope this exploration aids in diagnosing and comprehending complex systems based on their outputs and foundational inputs.