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This is a hierarchical Bayesian language model based on the Pitman-Yor process.

(define (pick-a-stick sticks J)
  (if (flip (sticks J))
      (pick-a-stick sticks (+ J 1))))

(define (make-PYP a b)
  (let ((sticks (mem (lambda (x) (beta (- 1.0 a) (+ b (* a x)))))))
    (lambda () (pick-a-stick sticks 1))))

(define (PYmem a b proc)
  (let ((augmented-proc (mem (lambda (args part) (apply proc args))))
        (crps (mem (lambda (args) (make-PYP a b)))))
    (lambda argsin (augmented-proc argsin ((crps argsin))))))

(define dictionary '(a b c d e f g))
(define max-ngram-order 4)
(define doc-length-hyper-param 10)

(define (kth-order-markov-memory K)
  (lambda (history update)
    (if (< (length history) K)
        (pair update history)
        (pair update (take history (- (length history) 1))))))

(define prefix->a (mem (lambda (prefix-length) (beta 1.0 1.0))))
(define prefix->b (mem (lambda (prefix-length) (gamma 1.0 1.0))))
(define draw-word (lambda () (uniform-draw dictionary)))

(define prefix->next-word-distribution
   (lambda (prefix) 
      (prefix->a (length prefix)) (prefix->b (length prefix))
      (lambda ()
        (if (null? prefix)
            (prefix->next-word (rest prefix))))))))

(define prefix->next-word
  (lambda (prefix)
    ((prefix->next-word-distribution prefix))))

(define (unfold-N N expander update-memory memory)
  (if (< N 1)
      (let ((next-symbol (expander memory)))
        (pair next-symbol
              (unfold-N (- N 1) 
                        (update-memory memory next-symbol))))))

(define doc->num-words 
   (lambda (doc) 
     (poisson doc-length-hyper-param))))

(define doc->words 
   (lambda (doc) 
      (doc->num-words doc) 
      (kth-order-markov-memory max-ngram-order) 

(doc->words 'doc1)

See also: